Research ArticleStudy of RF Signal Attenuation of Human Heart

Kedar Nath Sahu1 Challa Dhanunjaya Naidu2 M Satyam3 and K Jaya Sankar3

1Department of Electronics and Communication Engineering Stanley College of Engineering and Technology for WomenHyderabad Telangana 500 001 India2Department of Electronics and Communication Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabad Telangana 500 090 India3Department of Electronics and Communication Engineering Vasavi College of Engineering Hyderabad Telangana 500 031 India

Correspondence should be addressed to Kedar Nath Sahu knsahu72gmailcom

Received 28 July 2014 Revised 15 December 2014 Accepted 9 February 2015

Academic Editor Kamran Iqbal

Copyright copy 2015 Kedar Nath Sahu et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

A study of ultrawideband pulse propagation modeling through human body for all frequencies from 01 to 105 GHz is presentedReflection coefficient and signal attenuation are computed from themodel considering the variation of heart dimensionwith respectto time unlike a fixed dimension of heart used in earlier models The performance of cardiac activity is studied from the change ofsignal attenuation This estimation may help in the design of a noninvasive diagnostic system using ultrawideband of frequencies

1 Introduction

Human heartbeat performance is the basis for many modernpotential applications because it is impossible to suppressthe heartbeat related motion Some of the major applicationsinclude monitoring of heartbeat of a newborn infant in apediatric clinic burnt victims and remote monitoring of thehealth condition of a patient as well as the old people who areasleep As the heart involves a very small amplitude motionits detection becomes more challenging Any contact basedmethod for example an electrocardiogram (ECG) requiresa physical contact with the body of the human subject andhence is invasive However an invasive method suffers fromthe drawbacks such as being difficult to apply in case ofhuman infant subjects who are very susceptible to suddeninfant death syndrome (SIDS) intolerance of placing elec-trodes on the body of burnt victims problem of countermea-sures and the effect on the autonomic nervous system (ANS)during lie detection Detection andor monitoring of cardiacperformance using ultrawideband (UWB) radar technique isbecoming of great importance as it is noninvasive and remoteFurthermore UWB radars have several special featuressuch as environmental friendliness very low electromagneticenergy emission high miniaturization capability very low

cost and high resolution UWB radar transmits a sequenceof very short pulses over a large bandwidth unlike thecontinuous-wave (CW) radars which transmit a continuous-wave signal at a particular frequency The radio frequency(RF) signal returned to the radar receiver after being reflectedfrom the human subject contains the information about thefunctional pattern of the human heartTherefore the study ofUWB wave propagation aspects into a human thorax modelhelps to obtain the state of the human heart The model pre-dicted estimation will be useful to estimate how much poweris needed for a specific purpose and also to get an indicationas to whether the person is living or dead The accuracyof a study of this kind depends on an appropriate and effectivepropagation model

UWB propagation into the layered models developedearlier [1 2] was identified for not considering the effect ofmultiple reflections In our previous work [3] propagationof UWB pulses in the human tissues was studied for a fixedradar system placed on the room wall at a distance of onemeter from the subject to be monitored A multilayer planarmodel of human thorax was used to predict UWB signalattenuation considering signal propagation on the air-skin-heart-air path The multilayered model used the frequencydependent dielectric properties of layered tissue mediums

Hindawi Publishing CorporationJournal of EngineeringVolume 2015 Article ID 484686 8 pageshttpdxdoiorg1011552015484686

2 Journal of Engineering

Rightventricle

Left ventricle

Septum

Aortic valve

Left atrium

Right atrium

Pulmonary artery

Pulmonary vein

Mitral valve

Aorta

Superior vena cava

Pulmonary valve

Tricuspid valve

Interior vena cava

Figure 1 Transverse section of human heart [5]

over an ultrawideband similar to the frequency dependentmodel developed by [2] but was distinct due to the factthat the issue of multiple reflections ignored by the earliermodels [1 2] was accounted for by developing the impedancetransformation model This earlier idea was to develop areasonably simple radar and the signal attenuation analysiswas done up to the heart tissue in the thorax model But elec-tromagnetic energy leaks to the tissues through and beyondthe heart up to the posterior skin aswellTherefore the tissuesbeyond heart also contribute further to the signal attenuationwhich needs to be studied A similar kind of model thatconsidered tissues up to the posterior skin as well as theinclusion of the effect of multiple reflections was found in theliterature [4]

In this paper we have extended the analysis by consider-ing a more standard anatomical full body model to developa multilayer planar model and the dispersive behavior ofelectromagnetic properties of human tissues In order toaccommodate the frequencies of the Federal Commission forCommunication (FCC) approved UWB (31 to 106GHz) thesignal attenuation is evaluated for typical frequencies from01to 105 GHz In order to validate the considered model thesignal attenuation as a function of frequencywill be evaluatedand compared with the results obtained in [2 4] Due tothe particular applications of UWB radar in medicine it isfundamental to investigate the propagation of UWB pulses inhuman tissues with reference to both the safety issues and thedetermination of optimum signal to monitor the cardiopul-monary activity

2 The Planar Thorax Model

In order to evaluate the propagation characteristics for variedheart dimensions the time dependence of heart motion wasstudied and described in the following section with a briefdescription about the constitution of heart

21 The Human Heart Structure This is a hollow coneshaped four-chambered (left and right atria left and rightventricles) muscle located between the lungs and behind thesternum Two-thirds of the heart is located to the left of themidline of the body and the remaining one-third is placedto the right According to the medical illustrations right andleft correspond to the personrsquos right and left assuming that theperson is looking at us

The transverse cross-sectional view of heart structure [5]as shown in Figure 1 consists of left ventricle wall left ventri-cle cavity interventricular septum right ventricle cavity andright ventricle wall The left ventricle (LV) and the right ven-tricle (RV) are the longer cavities in the human heartThe leftventricle has a thicker wall than the right ventricle

211 The Cardiac Cycle The heart function alternates be-tween contraction and relaxation in a concerted patterncalled the cardiac cycle One cardiac cycle consists of onecomplete diastole and one complete systole Diastole is thephase of the cardiac cycle during which the chambers of theheart relax and the ventricles dilate allowing the blood to flowin Systole is the phase of the cardiac cycle during which the

Journal of Engineering 3

ventricles contract pumping the blood into the aorta and thepulmonary artery At the start of the diastole the heartmuscleis relaxed and blood flows into the atria At the end of diastoleboth atria contract simultaneously and this helps to fill theventricles with blood immediately prior to the systole Onecardiac cycle is completed in 08 seconds (ie in less than onesecond) A systole is one complete contraction phase of thecardiac cycle and a diastole is one complete relaxation phase

212TheCardiac Dimension and Its Variation Theheart andits performance are commonly measured in terms of one-dimensional distancesThe left ventricle end diastole (LVED)is the length measured at the end of diastole (ie when theheart is fully relaxed) and normally corresponds to the largestcardiac dimension Similarly the left ventricle end systole(LVES) is the lengthmeasured at the end of systole (ie whenthe heart is fully contracted) and corresponds to the smallestcardiac dimension The ventricular cavity interventricularseptum ventricular-free wall thickness and their changeswith respect to time during the cardiac cycle have beenmeasured using various methods such as echocardiographyangiography and cine MRI as adopted in [6ndash12]The instan-taneous time of the dimensions and the time-rates of changein the wall thickness cavity area and transverse dimensionduring isovolumic relaxation (end-diastole) and contraction(end-systole) for normal subjects are estimated and reportedin [6] Results of the normal diameters of the cardiac cavitiesand the ventricular interventricular wall thickness values asreported in literature are mentioned as follows

The end-diastolic LV cavity wall thickness is 09 plusmn 02 cmwhich is almost close to the value 08 plusmn 02 cm as reportedin [9] increasing to 20 plusmn 05 cm at the end of systole [6]The LVED cavity diameter 49 plusmn 04 cm [7] is close to 516 plusmn046 cm [8] and 50mm [9] and consistent in the normalrange 33ndash5 cm of [7] At the end of systole the LV cavitygets a reduction of 22 plusmn 04 cm [6] and thus the cavitydiameter becomes about 27 cmThis value is as close as 338plusmn036 cm asmentioned in [7] 4 cm as in [8] and in the normalrange 278ndash54 cm as reported in [11] The thickness value ofinterventricular septum is 83mm which satisfies the normalrange of 7ndash11mm and is in consistency with 103 plusmn 05mmas reported in [10] The RV cavity diameter at the end ofdiastole is 371 plusmn 59mm that is 37 plusmn 059 cm and is equalto 28 cm at the end of systole as mentioned in [7] and itsadjacent wall (the posterior wall) thickness at the end ofdiastole is 08 plusmn 02 cm as found in [9] which is close to thevalue 102 plusmn 05mm as reported in [10] and correspondinglyat the end of systole this value is 13plusmn 02 cmas given in [9] Sofar as the rate of change of dimension (119889119863119889119905) is concernedthe peak systolic 119889119863119889119905 is 13 plusmn 5 cms and the peak diastolic119889119863119889119905 is 16 plusmn 4 cms as mentioned in [6] The total thicknessof heart at the end of diastole at the end of systole andduring the interval from the end of diastole to the end ofsystole is the sum of the instantaneous thickness values of leftventriclewall (anteriorwall) left ventricle (LV) cavity septumthickness right ventricle (RV) cavity and the right ventriclewall (posterior wall) Based on the changes of cavity dimen-sion wall thickness with time as well as their peak rates ofchange as reported in [6] the total heart size (in millimeter)

100

102

104

106

108

110

112

0 01 02 03 04 05 06 07 08

Hea

rt d

imen

sion

(mm

)

Time (s)

Figure 2 Variation of transverse dimension of normal human heartwith time during a cardiac cycle

Table 1 Instantaneous dimensions of human heart

Time (s) Heart size (mm) Heart activity0 1114 End of diastole and start of systole01 1037 Systole02 102303 1004 End of systole and start of diastole04 1028

Diastole05 106306 107807 108808 1114 End of diastole

during systole and diastole is obtained for one completecardiac cycle of 08 s as shown in Table 1 and depicted inFigure 2

22 Multilayered Human Thorax Model The model dis-cussed in [3] included a few major tissues from chest skin upto heart only for the study of signal attenuation In this workwe extended the analysis by including the significant tissuesbeyond the heart and right up to the posterior skin as shownin Figure 3

The same Visible Human Project based anatomical thick-ness values of the tissue layers as used in [1 3] are consideredfor this model The thickness of dry skin of 15mm averageinfiltrated fat of 96mm muscle of 135mm cartilage of116mm deflated lung of 578mm and the different heartthickness values corresponding to the different instants oftime of the cardiac cycle (Table 1) have been consideredThe same tissues of these thickness values are consideredbehind the heart as well The dispersive behavior of humantissues has been taken into account through the Cole-Colemodel using the parameters computed in Gabrielrsquos data bookof dielectric properties of tissues [13] and also reported in[14]The variations of the dispersive dielectric properties as afunction of frequency at all frequencies from 01 to 105 GHzare plotted as shown in Figure 4 It is seen that over theentire band of frequencies considered as the frequencyincreases the relative permittivity decreases (Figure 4(a)) butthe conductivity increases (Figure 4(b))This implies that theother propagation parameters such as attenuation constant

4 Journal of Engineering

Air

1000

Skin

15 96

Muscle

135

Cartilage

116

Lung

578

Heart Cartilage

116

Muscle

135

Fat

96

Skin

15

AirFat

(a)

Air

1000

Skin

15 96

Muscle

135

Cartilage

116

Lung

578

Heart Cartilage

116

Muscle

135

Fat

96

Skin

15

AirFat

(b)

Figure 3 Tissue structure for EM modeling of human body (a) forward propagation (b) backward propagation Figures in the diagramindicate the thickness of the tissue layers in millimeter

0

20

40

60

80

100

120

140

160

180

01 1 2 3 4 5 6 7 8 9 10 11

Rela

tive p

erm

ittiv

ity m

agni

tude

f (GHz)

SkinFatMuscleCartilage

Deflated lungInflated lungHeart

(a)

SkinFatMuscleCartilage

Deflated lungInflated lungHeart

0

2

4

6

8

10

12

14

01 1 2 3 4 5 6 7 8 9 10 11

Con

duct

ivity

(Sm

)

f (GHz)

(b)

Figure 4 Variation of (a) relative permittivity (b) conductivity of tissues with frequency

phase-shift constant magnitude of intrinsic impedance andwave velocity also increase with frequency

3 Analysis of UWB Pulse Propagation intothe Model

As biological tissues are lossy media from an electromagneticpoint of view they are characterized in terms of the propaga-tion parameters discussed in Section 22These characteristicparameters are highly frequency dependent The incidentreflected and transmitted powers at any interface of themultilayered thorax model (Figure 3) are the result of a netforward wave due to the multiple reflections taking place inthe previous interfaces and the reflected wave may be consid-ered as the effect of all themultiple reflections occurring at theboundary Therefore the net incident reflected and trans-mitted powers at all tissue interfaces are calculated at typicalfrequencies of the ultrawideband range from 01 to 105 GHz

using the following power relations given by (1) through (3)as described in [15]

Net incident power 119875+119894=

(119864+

1)2

21205781

(1)

Net reflected power 119875minus119903=

(Γ119864+

1)2

21205781

= |Γ|2(119864+

1)2

21205781

= |Γ|2

119875+

119894

(2)

Net transmitted power 119875+119905= (1 minus |Γ|

2

) 119875+

119894 (3)

where |Γ| is the reflection coefficient magnitude at an inter-face

In the event of the wave reflection from such multipleinterfaces the impedance transformation method considersthe complicated sequence of multiple reflections in everylayer as explained in [15] assuming the normal incidence

Journal of Engineering 5

n = 1 n = 2 n = 3

1205781 1205782 1205783 1205784

P+1i

P+1t

P+2i

P+2t

P+3i

P+3t

Pminus3r

Pminus2r

z = l2 + l3 z = l3 z = 0

120578in1 120578in2 120578in3 = 1205784

Z

Figure 5 Planar impedance transformationmodel for a three-inter-face four-layer case

of a plane wave on every interface A three-interface four-layer configuration of the planar impedance transformationmodel is as shown in Figure 5 Using the boundary conditionson either side of an interface the effective input impedanceoffered by all subsequent layers to the right of every interfacecan be computed as obtained in [15] The effective inputimpedance at the interfaces 119899 = 3 2 and 1 can be givenby (4) through (6) respectively Using the input impedancevalues calculated in this way the reflection coefficient canthen be calculated at every interface for example reflectioncoefficient at interface 1 can be as given by (7)

At interface 3 the effective input impedance is

120578in3 = 1205784 (4)

At interface 2 the effective input impedance is

120578in2 = 12057831205784cos12057331198973+ 1198951205783sin12057331198973

1205783cos12057331198973+ 1198951205784sin12057331198973

(5)

and at interface 1 the effective input impedance becomes

120578in1 = 1205782120578in2 cos12057321198972 + 1198951205782 sin120573211989721205782cos12057321198972+ 119895120578in2 sin12057321198972

(6)

Then reflection coefficient at interface 1 can be expressed as

Γ1=

120578in1 minus 1205781

120578in1 + 1205781 (7)

where 1205781 1205782 1205783 and 120578

4are the intrinsic impedances 120573

2and

1205733are the wave numbers of the respective layers 119897

2and 1198973are

the thickness values of layers 2 and 3 respectivelySimilarly considering the eleven-layered tissue system

model (Figure 3) the input impedance and the reflec-tion coefficient corresponding to every tissue interface areobtained using a MATLAB program

Thus in order to study the behavior of the backscatteredfield from a human body illuminated by the plane elec-tromagnetic waves from a radar transmitter we simplified

0

01

02

03

04

05 1

15 2

25 3

31

35 4

45 5

55 6

65 7

75 8

85 9

95 10

105

Refle

ctio

n co

effici

ent (

dB)

f (GHz)Reflection coefficient (dB)Five-point moving average

minus10

minus8

minus6

minus4

minus2

Figure 6 Reflection coefficient from heart at the end of diastole Afive-pointmoving average is superimposed for a clearer understand-ing

the problem by modeling the human body as a series ofbiological tissue layers of complex permittivity Knowingthe permittivity of the tissue materials and by utilizingthe basic principles of electromagnetic wave propagation inaccordancewith the physical processes the power received bythe radar receiver the reflection coefficients at every interfaceand signal power attenuation of the heart are determined

4 Results and Discussion

When the power carried by the radar wave is incident onany interface ldquo119899rdquo separating the two tissue mediums ldquo119899rdquo andldquo119899 + 1rdquo part of it is transmitted to the next layer in the sameforward direction known as the transmitted power and theremaining power is reflected into its previous layer in thebackward direction known as the reflected power compo-nent The amount of power reflected from every interfacekeeps getting retransmitted in a backward propagation modeand is finally received at the radar receiver Such retransmit-ted power components from each of the interfaces received bythe radar receiver in a backward propagationmode are calledthe backward reflected power The transmitted power or thereflected power respectively through or from every interfaceduring either mode of propagation forward or backward ismultiplied by the power attenuation factor of the correspond-ing layer before entering into the next tissue layer

(i) Reflection Coefficient The characteristic behavior of theincident and reflected signals at every tissue interface of theplanar eleven-layer model (Figure 3) based on the impedancetransformation approach as a function of frequency is com-puted using MATLAB Considering the completely relaxedstate of the heart at the end of diastole the variation ofreflection coefficient of heart wall with frequency is plottedas shown in Figure 6 A five-point moving average is super-imposed for clear understanding

It is observed that the average reflection coefficient isas close as minus3 dB (approximately) over the whole band offrequency This means that about half of the electromagneticpower incident on the model is reflected back and theother half is transmitted into the body Moreover the reflec-tion coefficient value is negative at any frequency becausethe impedance offered by the human body is less than

6 Journal of Engineering

0

0 01 02 03 04 05 06 07 08

Sign

al at

tenu

atio

n (d

B)

Time (s)

minus60

minus50

minus40

minus30

minus20

minus10

(a)

0 01 02 03 04 05 06 07 08Time (s)

0

Sign

al at

tenu

atio

n (d

B)

minus90

minus80

minus70

minus60

minus50

minus40

minus30

minus20

minus10

(b)

0 01 02 03 04 05 06 07 08Time (s)

Sign

al at

tenu

atio

n (d

B)

minus28minus30minus32minus34minus36minus38minus40minus42minus44minus46

(c)

Figure 7 Variation of signal attenuation with time at (a) 01 GHz (b) 05 GHz and (c) 1 GHz respectively

the impedance of free space This implies that the reflectedpulses have an inverse relationship with respect to theincident pulses

(ii) Signal Attenuation The backward reflected power fromthe heart wall (interface-6) that is the heart-lung interface(119875minus

6119903)1015840 out of the total power input at the chest surface

(interface-1) 119875119894 is defined as the signal attenuation due to the

UWB pulse echo for the frequencies in the entire band of01 to 105 GHz and can be determined by using (8) as givenbelow The attenuation factor product and the transmissioncoefficient product can be evaluated by using (9) and (10)respectively

(119875minus

6119903)1015840

=1003816100381610038161003816Γ6

1003816100381610038161003816

2

times (attenuation factor product)2

times (transmission coefficient product)2 119875119894

(8)

whereattenuation factor product

= 119890minus21205722ℓ2119890minus21205723ℓ3119890minus21205724ℓ4119890minus21205725ℓ5119890minus21205726ℓ6

(9)

transmission coefficient product

= [(1 minus1003816100381610038161003816Γ1

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ2

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ3

1003816100381610038161003816

2

)

sdot (1 minus1003816100381610038161003816Γ4

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ5

1003816100381610038161003816

2

)]

(10)

The subscripts 2 3 4 5 and 6 refer to the layers suchas skin fat muscle cartilage and lung respectively for

the calculation of the attenuation factor product and thesubscripts 1 2 3 4 and 5 refer to skin-fat fat-muscle muscle-cartilage cartilage-lung and lung-heart interfaces respec-tively for the calculation of the transmission coefficientproduct Thus the signal power attenuation is calculated forsome typical frequencies in the band of 01 to 105 GHz using(8) through (10)

The model predicted average attenuation is minus98 dB at31 GHz which is in good agreement with the attenuation ofminus93 dB at this frequency as predicted by [2] but for a differentthorax model Similarly the model predicted attenuationis minus978 dB at 3GHz and is in good agreement with theattenuation of minus100 dB at this frequency as predicted by [4]

At different instants of time in the cardiac cycle heartassumes different dimensions In other words the dimen-sions of the layer representing heart are related to the dimen-sion of heart Therefore the variation of attenuation withdimension is directly related to the variation of the heartdimensions with time Hence the attenuation characteristicfor different dimensions is related to the heart movementFigures 7(a) through 7(c) represent the variation of atten-uation for typical frequencies of 01 05 and 1GHz withtime respectively and the time has been associated with thewidth of the heart (Figure 2) Thus the period between themaximum attenuations corresponds to the heart beat periodIn the case of 01 GHz the minimum attenuation occurs atthe heart dimension equal to 1004mm corresponding tothe instant of 03 seconds and the maximum attenuationtakes place at 1114mm at the end of diastole as depicted inFigure 7(a) The similar behavior is also observed at other

Journal of Engineering 7

0

01

03

05

15

25

31 4 5 6 7 8 9 10

f (GHz)

Max

imum

at

tenu

atio

n (d

B)

Max attenuationFive-point moving average

minus350

minus300

minus250

minus200

minus150

minus100

minus50

(a)

f (GHz)Min attenuationFive-point moving average

0

01

03

05

15

25

31 4 5 6 7 8 9 10

Min

imum

at

tenu

atio

n (d

B)

minus250

minus200

minus150

minus100

minus50

(b)

Figure 8Variations of (a)maximumand (b)minimumsignal attenuationwith frequency Superimposed five-pointmoving average is plotted

frequencies for example 05 GHz 1 GHz and so forth asshown in Figures 7(b) and 7(c) respectively

This model predicted attenuation is obtained separatelyfor every instantaneously changing dimension of heart dur-ing the cardiac cycle It is found that there is a maximumand a minimum value of attenuation corresponding to everyfrequency in the band of 01 to 105 GHz as shown in Figure 8Superimposed is the five-point moving average plot It isobserved that the points of maximum and minimum atten-uation shift with frequency as depicted in Figures 8(a) and8(b) respectively

From this it may be noted that there is periodic variationin attenuation of an active heart at a given frequency Theperiodicity of attenuation characteristics (period betweenmaximum attenuation and minimum attenuation) refers tothe heartbeat period Knowing the period ofmaximumatten-uation or minimum attenuation one will be able to decidethe health of the heart Lack of periodicity might indicatethe problem of an unhealthy heartThis attenuationmeasure-ment can be carried out on persons who are not accessibleunlike other methods using stethoscope electrocardiograph(ECG) and so forth

5 Conclusions

Electromagnetic response of the human tissue is highlyfrequency dependent Of all the body tissues encountered inthe path of propagation heart is the onlymoving element thatcan have a noticeable displacement and all others are staticTherefore in the wake of the study of propagation charac-teristics that is signal attenuation and reflection coefficientwe focused computation of these parameters with chang-ing dimensions of heart during a complete cardiac cycleThen the change of attenuation and the reflection coefficientcorresponding to the change of heart size during relax-ation-contraction-relaxation (one cardiac cycle) at differentinstants of time during the cardiac period was studied Thiscan provide good information about the state of a personrsquosheart whether healthy or unhealthy Any noticeable changeof attenuation shall indicate that the person is live while nochange of attenuation found in this way might lead to anunusual guess that the person might be dead

In this paper we have presented a one-dimensionalelectromagnetic model of human body and incorporated theelectromagnetic properties of significant body tissues beyondheart corresponding to all frequencies from 01 to 105 GHz toaccommodate the FCC defined UWBMoreover the analysisis performed for changes with time of heart dimension notfor a fixed heart dimension as in earlier models A studyof variation of signal attenuation due to the instantaneouschange of heart dimensions during a cardiac cycle can pro-vide reliable information about the health of heart This fea-ture of change of signal attenuationmay also be used to studythe performance of cardiac activity of persons buried underthe rubbles of the debris of a collapsed building personsbehind a wall and so forth

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] EM Staderini ldquoUWB radars inmedicinerdquo IEEE Aerospace andElectronic Systems Magazine vol 17 no 1 pp 13ndash18 2002

[2] G Varotto and E M Staderini ldquoOn the UWB medical radarsworking principlesrdquo International Journal of Ultra WidebandCommunications and Systems vol 2 no 2 pp 83ndash93 2011

[3] K N Sahu C D Naidu and K Jaya Sankar ldquoFrequency depen-dent planar electromagnetic modeling of human body andtheoretical study on attenuation for budget estimation of UWBradarrdquo The Global Journal of Researches in Engineering vol 14no 3 pp 35ndash44 2014

[4] M Cavagnaro E Pittella and S Pisa ldquoUWB pulse propagationinto human tissuesrdquo Physics inMedicine and Biology vol 58 no24 pp 8689ndash8707 2013

[5] January 2010 httpwwwsciencekidsconzpictureshuman-bodyheartdiagramhtml

[6] D G Gibson T A Traill and D J Brown ldquoChanges in leftventricular free wall thickness in patients with ischaemic heartdiseaserdquo British Heart Journal vol 39 no 12 pp 1312ndash1318 1977

[7] K Hergan A Schuster M Mair R Burger and M TopkerldquoNormal cardiac diameters in cine-MRI of the heartrdquo RoFoFortschritte auf dem Gebiete der Rontgenstrahlen und der Nuk-learmedizin vol 176 no 11 pp 1599ndash1606 2004 (German)

8 Journal of Engineering

[8] January 2010 httpwwwstanfordedugroupccm echocardiocgi-binmediawikiindexphpLeft ventricle size

[9] T A Traill D G Gibson and D J Brown ldquoStudy of left ven-tricular wall thickness and dimension changes using echocar-diographyrdquo British Heart Journal vol 40 no 2 pp 162ndash1691978

[10] S Kaul G LWismer T J Brady et al ldquoMeasurement of normalleft heart dimensions using optimally oriented MR imagesrdquoAmerican Journal of Roentgenology vol 146 no 1 pp 75ndash791986

[11] L E Hudsmith S E Petersen J M Francis M D Robson andS Neubauer ldquoNormal human left and right ventricular and leftatrial dimensions using steady state free precession magneticresonance imagingrdquo Journal of Cardiovascular Magnetic Reso-nance vol 7 no 5 pp 775ndash782 2005

[12] R F Rushmer and N Thal ldquoThe mechanics of ventricularcontraction a Cinefluorographic Studyrdquo Circulation vol 4 no2 pp 219ndash228 1951

[13] C Gabriel ldquoCompilation of the dielectric properties of bodytissues at RF and microwave frequenciesrdquo Report ALOE-TR-1996-0037 Occupational and Environmental Health Direc-torate Radio Frequency Radiation Division Brooks Air ForceBase San Antonio Tex USA 1996

[14] Institute forApplied Physics ldquoAn Internet Resource forTheCal-culation of The Dielectric Properties of Body Tissuesrdquo ItalianNational Research Council httpniremfifaccnrittissprop

[15] W H Hayt and J A Buck Engineering Electromagnetics TataMcGraw-Hill Mumbai India 7th edition 2006

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2 Journal of Engineering

Rightventricle

Left ventricle

Septum

Aortic valve

Left atrium

Right atrium

Pulmonary artery

Pulmonary vein

Mitral valve

Aorta

Superior vena cava

Pulmonary valve

Tricuspid valve

Interior vena cava

Figure 1 Transverse section of human heart [5]

over an ultrawideband similar to the frequency dependentmodel developed by [2] but was distinct due to the factthat the issue of multiple reflections ignored by the earliermodels [1 2] was accounted for by developing the impedancetransformation model This earlier idea was to develop areasonably simple radar and the signal attenuation analysiswas done up to the heart tissue in the thorax model But elec-tromagnetic energy leaks to the tissues through and beyondthe heart up to the posterior skin aswellTherefore the tissuesbeyond heart also contribute further to the signal attenuationwhich needs to be studied A similar kind of model thatconsidered tissues up to the posterior skin as well as theinclusion of the effect of multiple reflections was found in theliterature [4]

In this paper we have extended the analysis by consider-ing a more standard anatomical full body model to developa multilayer planar model and the dispersive behavior ofelectromagnetic properties of human tissues In order toaccommodate the frequencies of the Federal Commission forCommunication (FCC) approved UWB (31 to 106GHz) thesignal attenuation is evaluated for typical frequencies from01to 105 GHz In order to validate the considered model thesignal attenuation as a function of frequencywill be evaluatedand compared with the results obtained in [2 4] Due tothe particular applications of UWB radar in medicine it isfundamental to investigate the propagation of UWB pulses inhuman tissues with reference to both the safety issues and thedetermination of optimum signal to monitor the cardiopul-monary activity

2 The Planar Thorax Model

In order to evaluate the propagation characteristics for variedheart dimensions the time dependence of heart motion wasstudied and described in the following section with a briefdescription about the constitution of heart

21 The Human Heart Structure This is a hollow coneshaped four-chambered (left and right atria left and rightventricles) muscle located between the lungs and behind thesternum Two-thirds of the heart is located to the left of themidline of the body and the remaining one-third is placedto the right According to the medical illustrations right andleft correspond to the personrsquos right and left assuming that theperson is looking at us

The transverse cross-sectional view of heart structure [5]as shown in Figure 1 consists of left ventricle wall left ventri-cle cavity interventricular septum right ventricle cavity andright ventricle wall The left ventricle (LV) and the right ven-tricle (RV) are the longer cavities in the human heartThe leftventricle has a thicker wall than the right ventricle

211 The Cardiac Cycle The heart function alternates be-tween contraction and relaxation in a concerted patterncalled the cardiac cycle One cardiac cycle consists of onecomplete diastole and one complete systole Diastole is thephase of the cardiac cycle during which the chambers of theheart relax and the ventricles dilate allowing the blood to flowin Systole is the phase of the cardiac cycle during which the

Journal of Engineering 3

ventricles contract pumping the blood into the aorta and thepulmonary artery At the start of the diastole the heartmuscleis relaxed and blood flows into the atria At the end of diastoleboth atria contract simultaneously and this helps to fill theventricles with blood immediately prior to the systole Onecardiac cycle is completed in 08 seconds (ie in less than onesecond) A systole is one complete contraction phase of thecardiac cycle and a diastole is one complete relaxation phase

212TheCardiac Dimension and Its Variation Theheart andits performance are commonly measured in terms of one-dimensional distancesThe left ventricle end diastole (LVED)is the length measured at the end of diastole (ie when theheart is fully relaxed) and normally corresponds to the largestcardiac dimension Similarly the left ventricle end systole(LVES) is the lengthmeasured at the end of systole (ie whenthe heart is fully contracted) and corresponds to the smallestcardiac dimension The ventricular cavity interventricularseptum ventricular-free wall thickness and their changeswith respect to time during the cardiac cycle have beenmeasured using various methods such as echocardiographyangiography and cine MRI as adopted in [6ndash12]The instan-taneous time of the dimensions and the time-rates of changein the wall thickness cavity area and transverse dimensionduring isovolumic relaxation (end-diastole) and contraction(end-systole) for normal subjects are estimated and reportedin [6] Results of the normal diameters of the cardiac cavitiesand the ventricular interventricular wall thickness values asreported in literature are mentioned as follows

The end-diastolic LV cavity wall thickness is 09 plusmn 02 cmwhich is almost close to the value 08 plusmn 02 cm as reportedin [9] increasing to 20 plusmn 05 cm at the end of systole [6]The LVED cavity diameter 49 plusmn 04 cm [7] is close to 516 plusmn046 cm [8] and 50mm [9] and consistent in the normalrange 33ndash5 cm of [7] At the end of systole the LV cavitygets a reduction of 22 plusmn 04 cm [6] and thus the cavitydiameter becomes about 27 cmThis value is as close as 338plusmn036 cm asmentioned in [7] 4 cm as in [8] and in the normalrange 278ndash54 cm as reported in [11] The thickness value ofinterventricular septum is 83mm which satisfies the normalrange of 7ndash11mm and is in consistency with 103 plusmn 05mmas reported in [10] The RV cavity diameter at the end ofdiastole is 371 plusmn 59mm that is 37 plusmn 059 cm and is equalto 28 cm at the end of systole as mentioned in [7] and itsadjacent wall (the posterior wall) thickness at the end ofdiastole is 08 plusmn 02 cm as found in [9] which is close to thevalue 102 plusmn 05mm as reported in [10] and correspondinglyat the end of systole this value is 13plusmn 02 cmas given in [9] Sofar as the rate of change of dimension (119889119863119889119905) is concernedthe peak systolic 119889119863119889119905 is 13 plusmn 5 cms and the peak diastolic119889119863119889119905 is 16 plusmn 4 cms as mentioned in [6] The total thicknessof heart at the end of diastole at the end of systole andduring the interval from the end of diastole to the end ofsystole is the sum of the instantaneous thickness values of leftventriclewall (anteriorwall) left ventricle (LV) cavity septumthickness right ventricle (RV) cavity and the right ventriclewall (posterior wall) Based on the changes of cavity dimen-sion wall thickness with time as well as their peak rates ofchange as reported in [6] the total heart size (in millimeter)

100

102

104

106

108

110

112

0 01 02 03 04 05 06 07 08

Hea

rt d

imen

sion

(mm

)

Time (s)

Figure 2 Variation of transverse dimension of normal human heartwith time during a cardiac cycle

Table 1 Instantaneous dimensions of human heart

Time (s) Heart size (mm) Heart activity0 1114 End of diastole and start of systole01 1037 Systole02 102303 1004 End of systole and start of diastole04 1028

Diastole05 106306 107807 108808 1114 End of diastole

during systole and diastole is obtained for one completecardiac cycle of 08 s as shown in Table 1 and depicted inFigure 2

22 Multilayered Human Thorax Model The model dis-cussed in [3] included a few major tissues from chest skin upto heart only for the study of signal attenuation In this workwe extended the analysis by including the significant tissuesbeyond the heart and right up to the posterior skin as shownin Figure 3

The same Visible Human Project based anatomical thick-ness values of the tissue layers as used in [1 3] are consideredfor this model The thickness of dry skin of 15mm averageinfiltrated fat of 96mm muscle of 135mm cartilage of116mm deflated lung of 578mm and the different heartthickness values corresponding to the different instants oftime of the cardiac cycle (Table 1) have been consideredThe same tissues of these thickness values are consideredbehind the heart as well The dispersive behavior of humantissues has been taken into account through the Cole-Colemodel using the parameters computed in Gabrielrsquos data bookof dielectric properties of tissues [13] and also reported in[14]The variations of the dispersive dielectric properties as afunction of frequency at all frequencies from 01 to 105 GHzare plotted as shown in Figure 4 It is seen that over theentire band of frequencies considered as the frequencyincreases the relative permittivity decreases (Figure 4(a)) butthe conductivity increases (Figure 4(b))This implies that theother propagation parameters such as attenuation constant

4 Journal of Engineering

Air

1000

Skin

15 96

Muscle

135

Cartilage

116

Lung

578

Heart Cartilage

116

Muscle

135

Fat

96

Skin

15

AirFat

(a)

Air

1000

Skin

15 96

Muscle

135

Cartilage

116

Lung

578

Heart Cartilage

116

Muscle

135

Fat

96

Skin

15

AirFat

(b)

Figure 3 Tissue structure for EM modeling of human body (a) forward propagation (b) backward propagation Figures in the diagramindicate the thickness of the tissue layers in millimeter

0

20

40

60

80

100

120

140

160

180

01 1 2 3 4 5 6 7 8 9 10 11

Rela

tive p

erm

ittiv

ity m

agni

tude

f (GHz)

SkinFatMuscleCartilage

Deflated lungInflated lungHeart

(a)

SkinFatMuscleCartilage

Deflated lungInflated lungHeart

0

2

4

6

8

10

12

14

01 1 2 3 4 5 6 7 8 9 10 11

Con

duct

ivity

(Sm

)

f (GHz)

(b)

Figure 4 Variation of (a) relative permittivity (b) conductivity of tissues with frequency

phase-shift constant magnitude of intrinsic impedance andwave velocity also increase with frequency

3 Analysis of UWB Pulse Propagation intothe Model

As biological tissues are lossy media from an electromagneticpoint of view they are characterized in terms of the propaga-tion parameters discussed in Section 22These characteristicparameters are highly frequency dependent The incidentreflected and transmitted powers at any interface of themultilayered thorax model (Figure 3) are the result of a netforward wave due to the multiple reflections taking place inthe previous interfaces and the reflected wave may be consid-ered as the effect of all themultiple reflections occurring at theboundary Therefore the net incident reflected and trans-mitted powers at all tissue interfaces are calculated at typicalfrequencies of the ultrawideband range from 01 to 105 GHz

using the following power relations given by (1) through (3)as described in [15]

Net incident power 119875+119894=

(119864+

1)2

21205781

(1)

Net reflected power 119875minus119903=

(Γ119864+

1)2

21205781

= |Γ|2(119864+

1)2

21205781

= |Γ|2

119875+

119894

(2)

Net transmitted power 119875+119905= (1 minus |Γ|

2

) 119875+

119894 (3)

where |Γ| is the reflection coefficient magnitude at an inter-face

In the event of the wave reflection from such multipleinterfaces the impedance transformation method considersthe complicated sequence of multiple reflections in everylayer as explained in [15] assuming the normal incidence

Journal of Engineering 5

n = 1 n = 2 n = 3

1205781 1205782 1205783 1205784

P+1i

P+1t

P+2i

P+2t

P+3i

P+3t

Pminus3r

Pminus2r

z = l2 + l3 z = l3 z = 0

120578in1 120578in2 120578in3 = 1205784

Z

Figure 5 Planar impedance transformationmodel for a three-inter-face four-layer case

of a plane wave on every interface A three-interface four-layer configuration of the planar impedance transformationmodel is as shown in Figure 5 Using the boundary conditionson either side of an interface the effective input impedanceoffered by all subsequent layers to the right of every interfacecan be computed as obtained in [15] The effective inputimpedance at the interfaces 119899 = 3 2 and 1 can be givenby (4) through (6) respectively Using the input impedancevalues calculated in this way the reflection coefficient canthen be calculated at every interface for example reflectioncoefficient at interface 1 can be as given by (7)

At interface 3 the effective input impedance is

120578in3 = 1205784 (4)

At interface 2 the effective input impedance is

120578in2 = 12057831205784cos12057331198973+ 1198951205783sin12057331198973

1205783cos12057331198973+ 1198951205784sin12057331198973

(5)

and at interface 1 the effective input impedance becomes

120578in1 = 1205782120578in2 cos12057321198972 + 1198951205782 sin120573211989721205782cos12057321198972+ 119895120578in2 sin12057321198972

(6)

Then reflection coefficient at interface 1 can be expressed as

Γ1=

120578in1 minus 1205781

120578in1 + 1205781 (7)

where 1205781 1205782 1205783 and 120578

4are the intrinsic impedances 120573

2and

1205733are the wave numbers of the respective layers 119897

2and 1198973are

the thickness values of layers 2 and 3 respectivelySimilarly considering the eleven-layered tissue system

model (Figure 3) the input impedance and the reflec-tion coefficient corresponding to every tissue interface areobtained using a MATLAB program

Thus in order to study the behavior of the backscatteredfield from a human body illuminated by the plane elec-tromagnetic waves from a radar transmitter we simplified

0

01

02

03

04

05 1

15 2

25 3

31

35 4

45 5

55 6

65 7

75 8

85 9

95 10

105

Refle

ctio

n co

effici

ent (

dB)

f (GHz)Reflection coefficient (dB)Five-point moving average

minus10

minus8

minus6

minus4

minus2

Figure 6 Reflection coefficient from heart at the end of diastole Afive-pointmoving average is superimposed for a clearer understand-ing

the problem by modeling the human body as a series ofbiological tissue layers of complex permittivity Knowingthe permittivity of the tissue materials and by utilizingthe basic principles of electromagnetic wave propagation inaccordancewith the physical processes the power received bythe radar receiver the reflection coefficients at every interfaceand signal power attenuation of the heart are determined

4 Results and Discussion

When the power carried by the radar wave is incident onany interface ldquo119899rdquo separating the two tissue mediums ldquo119899rdquo andldquo119899 + 1rdquo part of it is transmitted to the next layer in the sameforward direction known as the transmitted power and theremaining power is reflected into its previous layer in thebackward direction known as the reflected power compo-nent The amount of power reflected from every interfacekeeps getting retransmitted in a backward propagation modeand is finally received at the radar receiver Such retransmit-ted power components from each of the interfaces received bythe radar receiver in a backward propagationmode are calledthe backward reflected power The transmitted power or thereflected power respectively through or from every interfaceduring either mode of propagation forward or backward ismultiplied by the power attenuation factor of the correspond-ing layer before entering into the next tissue layer

(i) Reflection Coefficient The characteristic behavior of theincident and reflected signals at every tissue interface of theplanar eleven-layer model (Figure 3) based on the impedancetransformation approach as a function of frequency is com-puted using MATLAB Considering the completely relaxedstate of the heart at the end of diastole the variation ofreflection coefficient of heart wall with frequency is plottedas shown in Figure 6 A five-point moving average is super-imposed for clear understanding

It is observed that the average reflection coefficient isas close as minus3 dB (approximately) over the whole band offrequency This means that about half of the electromagneticpower incident on the model is reflected back and theother half is transmitted into the body Moreover the reflec-tion coefficient value is negative at any frequency becausethe impedance offered by the human body is less than

6 Journal of Engineering

0

0 01 02 03 04 05 06 07 08

Sign

al at

tenu

atio

n (d

B)

Time (s)

minus60

minus50

minus40

minus30

minus20

minus10

(a)

0 01 02 03 04 05 06 07 08Time (s)

0

Sign

al at

tenu

atio

n (d

B)

minus90

minus80

minus70

minus60

minus50

minus40

minus30

minus20

minus10

(b)

0 01 02 03 04 05 06 07 08Time (s)

Sign

al at

tenu

atio

n (d

B)

minus28minus30minus32minus34minus36minus38minus40minus42minus44minus46

(c)

Figure 7 Variation of signal attenuation with time at (a) 01 GHz (b) 05 GHz and (c) 1 GHz respectively

the impedance of free space This implies that the reflectedpulses have an inverse relationship with respect to theincident pulses

(ii) Signal Attenuation The backward reflected power fromthe heart wall (interface-6) that is the heart-lung interface(119875minus

6119903)1015840 out of the total power input at the chest surface

(interface-1) 119875119894 is defined as the signal attenuation due to the

UWB pulse echo for the frequencies in the entire band of01 to 105 GHz and can be determined by using (8) as givenbelow The attenuation factor product and the transmissioncoefficient product can be evaluated by using (9) and (10)respectively

(119875minus

6119903)1015840

=1003816100381610038161003816Γ6

1003816100381610038161003816

2

times (attenuation factor product)2

times (transmission coefficient product)2 119875119894

(8)

whereattenuation factor product

= 119890minus21205722ℓ2119890minus21205723ℓ3119890minus21205724ℓ4119890minus21205725ℓ5119890minus21205726ℓ6

(9)

transmission coefficient product

= [(1 minus1003816100381610038161003816Γ1

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ2

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ3

1003816100381610038161003816

2

)

sdot (1 minus1003816100381610038161003816Γ4

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ5

1003816100381610038161003816

2

)]

(10)

The subscripts 2 3 4 5 and 6 refer to the layers suchas skin fat muscle cartilage and lung respectively for

the calculation of the attenuation factor product and thesubscripts 1 2 3 4 and 5 refer to skin-fat fat-muscle muscle-cartilage cartilage-lung and lung-heart interfaces respec-tively for the calculation of the transmission coefficientproduct Thus the signal power attenuation is calculated forsome typical frequencies in the band of 01 to 105 GHz using(8) through (10)

The model predicted average attenuation is minus98 dB at31 GHz which is in good agreement with the attenuation ofminus93 dB at this frequency as predicted by [2] but for a differentthorax model Similarly the model predicted attenuationis minus978 dB at 3GHz and is in good agreement with theattenuation of minus100 dB at this frequency as predicted by [4]

At different instants of time in the cardiac cycle heartassumes different dimensions In other words the dimen-sions of the layer representing heart are related to the dimen-sion of heart Therefore the variation of attenuation withdimension is directly related to the variation of the heartdimensions with time Hence the attenuation characteristicfor different dimensions is related to the heart movementFigures 7(a) through 7(c) represent the variation of atten-uation for typical frequencies of 01 05 and 1GHz withtime respectively and the time has been associated with thewidth of the heart (Figure 2) Thus the period between themaximum attenuations corresponds to the heart beat periodIn the case of 01 GHz the minimum attenuation occurs atthe heart dimension equal to 1004mm corresponding tothe instant of 03 seconds and the maximum attenuationtakes place at 1114mm at the end of diastole as depicted inFigure 7(a) The similar behavior is also observed at other

Journal of Engineering 7

0

01

03

05

15

25

31 4 5 6 7 8 9 10

f (GHz)

Max

imum

at

tenu

atio

n (d

B)

Max attenuationFive-point moving average

minus350

minus300

minus250

minus200

minus150

minus100

minus50

(a)

f (GHz)Min attenuationFive-point moving average

0

01

03

05

15

25

31 4 5 6 7 8 9 10

Min

imum

at

tenu

atio

n (d

B)

minus250

minus200

minus150

minus100

minus50

(b)

Figure 8Variations of (a)maximumand (b)minimumsignal attenuationwith frequency Superimposed five-pointmoving average is plotted

frequencies for example 05 GHz 1 GHz and so forth asshown in Figures 7(b) and 7(c) respectively

This model predicted attenuation is obtained separatelyfor every instantaneously changing dimension of heart dur-ing the cardiac cycle It is found that there is a maximumand a minimum value of attenuation corresponding to everyfrequency in the band of 01 to 105 GHz as shown in Figure 8Superimposed is the five-point moving average plot It isobserved that the points of maximum and minimum atten-uation shift with frequency as depicted in Figures 8(a) and8(b) respectively

From this it may be noted that there is periodic variationin attenuation of an active heart at a given frequency Theperiodicity of attenuation characteristics (period betweenmaximum attenuation and minimum attenuation) refers tothe heartbeat period Knowing the period ofmaximumatten-uation or minimum attenuation one will be able to decidethe health of the heart Lack of periodicity might indicatethe problem of an unhealthy heartThis attenuationmeasure-ment can be carried out on persons who are not accessibleunlike other methods using stethoscope electrocardiograph(ECG) and so forth

5 Conclusions

Electromagnetic response of the human tissue is highlyfrequency dependent Of all the body tissues encountered inthe path of propagation heart is the onlymoving element thatcan have a noticeable displacement and all others are staticTherefore in the wake of the study of propagation charac-teristics that is signal attenuation and reflection coefficientwe focused computation of these parameters with chang-ing dimensions of heart during a complete cardiac cycleThen the change of attenuation and the reflection coefficientcorresponding to the change of heart size during relax-ation-contraction-relaxation (one cardiac cycle) at differentinstants of time during the cardiac period was studied Thiscan provide good information about the state of a personrsquosheart whether healthy or unhealthy Any noticeable changeof attenuation shall indicate that the person is live while nochange of attenuation found in this way might lead to anunusual guess that the person might be dead

In this paper we have presented a one-dimensionalelectromagnetic model of human body and incorporated theelectromagnetic properties of significant body tissues beyondheart corresponding to all frequencies from 01 to 105 GHz toaccommodate the FCC defined UWBMoreover the analysisis performed for changes with time of heart dimension notfor a fixed heart dimension as in earlier models A studyof variation of signal attenuation due to the instantaneouschange of heart dimensions during a cardiac cycle can pro-vide reliable information about the health of heart This fea-ture of change of signal attenuationmay also be used to studythe performance of cardiac activity of persons buried underthe rubbles of the debris of a collapsed building personsbehind a wall and so forth

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] EM Staderini ldquoUWB radars inmedicinerdquo IEEE Aerospace andElectronic Systems Magazine vol 17 no 1 pp 13ndash18 2002

[2] G Varotto and E M Staderini ldquoOn the UWB medical radarsworking principlesrdquo International Journal of Ultra WidebandCommunications and Systems vol 2 no 2 pp 83ndash93 2011

[3] K N Sahu C D Naidu and K Jaya Sankar ldquoFrequency depen-dent planar electromagnetic modeling of human body andtheoretical study on attenuation for budget estimation of UWBradarrdquo The Global Journal of Researches in Engineering vol 14no 3 pp 35ndash44 2014

[4] M Cavagnaro E Pittella and S Pisa ldquoUWB pulse propagationinto human tissuesrdquo Physics inMedicine and Biology vol 58 no24 pp 8689ndash8707 2013

[5] January 2010 httpwwwsciencekidsconzpictureshuman-bodyheartdiagramhtml

[6] D G Gibson T A Traill and D J Brown ldquoChanges in leftventricular free wall thickness in patients with ischaemic heartdiseaserdquo British Heart Journal vol 39 no 12 pp 1312ndash1318 1977

[7] K Hergan A Schuster M Mair R Burger and M TopkerldquoNormal cardiac diameters in cine-MRI of the heartrdquo RoFoFortschritte auf dem Gebiete der Rontgenstrahlen und der Nuk-learmedizin vol 176 no 11 pp 1599ndash1606 2004 (German)

8 Journal of Engineering

[8] January 2010 httpwwwstanfordedugroupccm echocardiocgi-binmediawikiindexphpLeft ventricle size

[9] T A Traill D G Gibson and D J Brown ldquoStudy of left ven-tricular wall thickness and dimension changes using echocar-diographyrdquo British Heart Journal vol 40 no 2 pp 162ndash1691978

[10] S Kaul G LWismer T J Brady et al ldquoMeasurement of normalleft heart dimensions using optimally oriented MR imagesrdquoAmerican Journal of Roentgenology vol 146 no 1 pp 75ndash791986

[11] L E Hudsmith S E Petersen J M Francis M D Robson andS Neubauer ldquoNormal human left and right ventricular and leftatrial dimensions using steady state free precession magneticresonance imagingrdquo Journal of Cardiovascular Magnetic Reso-nance vol 7 no 5 pp 775ndash782 2005

[12] R F Rushmer and N Thal ldquoThe mechanics of ventricularcontraction a Cinefluorographic Studyrdquo Circulation vol 4 no2 pp 219ndash228 1951

[13] C Gabriel ldquoCompilation of the dielectric properties of bodytissues at RF and microwave frequenciesrdquo Report ALOE-TR-1996-0037 Occupational and Environmental Health Direc-torate Radio Frequency Radiation Division Brooks Air ForceBase San Antonio Tex USA 1996

[14] Institute forApplied Physics ldquoAn Internet Resource forTheCal-culation of The Dielectric Properties of Body Tissuesrdquo ItalianNational Research Council httpniremfifaccnrittissprop

[15] W H Hayt and J A Buck Engineering Electromagnetics TataMcGraw-Hill Mumbai India 7th edition 2006

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Journal of Engineering 3

ventricles contract pumping the blood into the aorta and thepulmonary artery At the start of the diastole the heartmuscleis relaxed and blood flows into the atria At the end of diastoleboth atria contract simultaneously and this helps to fill theventricles with blood immediately prior to the systole Onecardiac cycle is completed in 08 seconds (ie in less than onesecond) A systole is one complete contraction phase of thecardiac cycle and a diastole is one complete relaxation phase

212TheCardiac Dimension and Its Variation Theheart andits performance are commonly measured in terms of one-dimensional distancesThe left ventricle end diastole (LVED)is the length measured at the end of diastole (ie when theheart is fully relaxed) and normally corresponds to the largestcardiac dimension Similarly the left ventricle end systole(LVES) is the lengthmeasured at the end of systole (ie whenthe heart is fully contracted) and corresponds to the smallestcardiac dimension The ventricular cavity interventricularseptum ventricular-free wall thickness and their changeswith respect to time during the cardiac cycle have beenmeasured using various methods such as echocardiographyangiography and cine MRI as adopted in [6ndash12]The instan-taneous time of the dimensions and the time-rates of changein the wall thickness cavity area and transverse dimensionduring isovolumic relaxation (end-diastole) and contraction(end-systole) for normal subjects are estimated and reportedin [6] Results of the normal diameters of the cardiac cavitiesand the ventricular interventricular wall thickness values asreported in literature are mentioned as follows

The end-diastolic LV cavity wall thickness is 09 plusmn 02 cmwhich is almost close to the value 08 plusmn 02 cm as reportedin [9] increasing to 20 plusmn 05 cm at the end of systole [6]The LVED cavity diameter 49 plusmn 04 cm [7] is close to 516 plusmn046 cm [8] and 50mm [9] and consistent in the normalrange 33ndash5 cm of [7] At the end of systole the LV cavitygets a reduction of 22 plusmn 04 cm [6] and thus the cavitydiameter becomes about 27 cmThis value is as close as 338plusmn036 cm asmentioned in [7] 4 cm as in [8] and in the normalrange 278ndash54 cm as reported in [11] The thickness value ofinterventricular septum is 83mm which satisfies the normalrange of 7ndash11mm and is in consistency with 103 plusmn 05mmas reported in [10] The RV cavity diameter at the end ofdiastole is 371 plusmn 59mm that is 37 plusmn 059 cm and is equalto 28 cm at the end of systole as mentioned in [7] and itsadjacent wall (the posterior wall) thickness at the end ofdiastole is 08 plusmn 02 cm as found in [9] which is close to thevalue 102 plusmn 05mm as reported in [10] and correspondinglyat the end of systole this value is 13plusmn 02 cmas given in [9] Sofar as the rate of change of dimension (119889119863119889119905) is concernedthe peak systolic 119889119863119889119905 is 13 plusmn 5 cms and the peak diastolic119889119863119889119905 is 16 plusmn 4 cms as mentioned in [6] The total thicknessof heart at the end of diastole at the end of systole andduring the interval from the end of diastole to the end ofsystole is the sum of the instantaneous thickness values of leftventriclewall (anteriorwall) left ventricle (LV) cavity septumthickness right ventricle (RV) cavity and the right ventriclewall (posterior wall) Based on the changes of cavity dimen-sion wall thickness with time as well as their peak rates ofchange as reported in [6] the total heart size (in millimeter)

100

102

104

106

108

110

112

0 01 02 03 04 05 06 07 08

Hea

rt d

imen

sion

(mm

)

Time (s)

Figure 2 Variation of transverse dimension of normal human heartwith time during a cardiac cycle

Table 1 Instantaneous dimensions of human heart

Time (s) Heart size (mm) Heart activity0 1114 End of diastole and start of systole01 1037 Systole02 102303 1004 End of systole and start of diastole04 1028

Diastole05 106306 107807 108808 1114 End of diastole

during systole and diastole is obtained for one completecardiac cycle of 08 s as shown in Table 1 and depicted inFigure 2

22 Multilayered Human Thorax Model The model dis-cussed in [3] included a few major tissues from chest skin upto heart only for the study of signal attenuation In this workwe extended the analysis by including the significant tissuesbeyond the heart and right up to the posterior skin as shownin Figure 3

The same Visible Human Project based anatomical thick-ness values of the tissue layers as used in [1 3] are consideredfor this model The thickness of dry skin of 15mm averageinfiltrated fat of 96mm muscle of 135mm cartilage of116mm deflated lung of 578mm and the different heartthickness values corresponding to the different instants oftime of the cardiac cycle (Table 1) have been consideredThe same tissues of these thickness values are consideredbehind the heart as well The dispersive behavior of humantissues has been taken into account through the Cole-Colemodel using the parameters computed in Gabrielrsquos data bookof dielectric properties of tissues [13] and also reported in[14]The variations of the dispersive dielectric properties as afunction of frequency at all frequencies from 01 to 105 GHzare plotted as shown in Figure 4 It is seen that over theentire band of frequencies considered as the frequencyincreases the relative permittivity decreases (Figure 4(a)) butthe conductivity increases (Figure 4(b))This implies that theother propagation parameters such as attenuation constant

4 Journal of Engineering

Air

1000

Skin

15 96

Muscle

135

Cartilage

116

Lung

578

Heart Cartilage

116

Muscle

135

Fat

96

Skin

15

AirFat

(a)

Air

1000

Skin

15 96

Muscle

135

Cartilage

116

Lung

578

Heart Cartilage

116

Muscle

135

Fat

96

Skin

15

AirFat

(b)

Figure 3 Tissue structure for EM modeling of human body (a) forward propagation (b) backward propagation Figures in the diagramindicate the thickness of the tissue layers in millimeter

0

20

40

60

80

100

120

140

160

180

01 1 2 3 4 5 6 7 8 9 10 11

Rela

tive p

erm

ittiv

ity m

agni

tude

f (GHz)

SkinFatMuscleCartilage

Deflated lungInflated lungHeart

(a)

SkinFatMuscleCartilage

Deflated lungInflated lungHeart

0

2

4

6

8

10

12

14

01 1 2 3 4 5 6 7 8 9 10 11

Con

duct

ivity

(Sm

)

f (GHz)

(b)

Figure 4 Variation of (a) relative permittivity (b) conductivity of tissues with frequency

phase-shift constant magnitude of intrinsic impedance andwave velocity also increase with frequency

3 Analysis of UWB Pulse Propagation intothe Model

As biological tissues are lossy media from an electromagneticpoint of view they are characterized in terms of the propaga-tion parameters discussed in Section 22These characteristicparameters are highly frequency dependent The incidentreflected and transmitted powers at any interface of themultilayered thorax model (Figure 3) are the result of a netforward wave due to the multiple reflections taking place inthe previous interfaces and the reflected wave may be consid-ered as the effect of all themultiple reflections occurring at theboundary Therefore the net incident reflected and trans-mitted powers at all tissue interfaces are calculated at typicalfrequencies of the ultrawideband range from 01 to 105 GHz

using the following power relations given by (1) through (3)as described in [15]

Net incident power 119875+119894=

(119864+

1)2

21205781

(1)

Net reflected power 119875minus119903=

(Γ119864+

1)2

21205781

= |Γ|2(119864+

1)2

21205781

= |Γ|2

119875+

119894

(2)

Net transmitted power 119875+119905= (1 minus |Γ|

2

) 119875+

119894 (3)

where |Γ| is the reflection coefficient magnitude at an inter-face

In the event of the wave reflection from such multipleinterfaces the impedance transformation method considersthe complicated sequence of multiple reflections in everylayer as explained in [15] assuming the normal incidence

Journal of Engineering 5

n = 1 n = 2 n = 3

1205781 1205782 1205783 1205784

P+1i

P+1t

P+2i

P+2t

P+3i

P+3t

Pminus3r

Pminus2r

z = l2 + l3 z = l3 z = 0

120578in1 120578in2 120578in3 = 1205784

Z

Figure 5 Planar impedance transformationmodel for a three-inter-face four-layer case

of a plane wave on every interface A three-interface four-layer configuration of the planar impedance transformationmodel is as shown in Figure 5 Using the boundary conditionson either side of an interface the effective input impedanceoffered by all subsequent layers to the right of every interfacecan be computed as obtained in [15] The effective inputimpedance at the interfaces 119899 = 3 2 and 1 can be givenby (4) through (6) respectively Using the input impedancevalues calculated in this way the reflection coefficient canthen be calculated at every interface for example reflectioncoefficient at interface 1 can be as given by (7)

At interface 3 the effective input impedance is

120578in3 = 1205784 (4)

At interface 2 the effective input impedance is

120578in2 = 12057831205784cos12057331198973+ 1198951205783sin12057331198973

1205783cos12057331198973+ 1198951205784sin12057331198973

(5)

and at interface 1 the effective input impedance becomes

120578in1 = 1205782120578in2 cos12057321198972 + 1198951205782 sin120573211989721205782cos12057321198972+ 119895120578in2 sin12057321198972

(6)

Then reflection coefficient at interface 1 can be expressed as

Γ1=

120578in1 minus 1205781

120578in1 + 1205781 (7)

where 1205781 1205782 1205783 and 120578

4are the intrinsic impedances 120573

2and

1205733are the wave numbers of the respective layers 119897

2and 1198973are

the thickness values of layers 2 and 3 respectivelySimilarly considering the eleven-layered tissue system

model (Figure 3) the input impedance and the reflec-tion coefficient corresponding to every tissue interface areobtained using a MATLAB program

Thus in order to study the behavior of the backscatteredfield from a human body illuminated by the plane elec-tromagnetic waves from a radar transmitter we simplified

0

01

02

03

04

05 1

15 2

25 3

31

35 4

45 5

55 6

65 7

75 8

85 9

95 10

105

Refle

ctio

n co

effici

ent (

dB)

f (GHz)Reflection coefficient (dB)Five-point moving average

minus10

minus8

minus6

minus4

minus2

Figure 6 Reflection coefficient from heart at the end of diastole Afive-pointmoving average is superimposed for a clearer understand-ing

the problem by modeling the human body as a series ofbiological tissue layers of complex permittivity Knowingthe permittivity of the tissue materials and by utilizingthe basic principles of electromagnetic wave propagation inaccordancewith the physical processes the power received bythe radar receiver the reflection coefficients at every interfaceand signal power attenuation of the heart are determined

4 Results and Discussion

When the power carried by the radar wave is incident onany interface ldquo119899rdquo separating the two tissue mediums ldquo119899rdquo andldquo119899 + 1rdquo part of it is transmitted to the next layer in the sameforward direction known as the transmitted power and theremaining power is reflected into its previous layer in thebackward direction known as the reflected power compo-nent The amount of power reflected from every interfacekeeps getting retransmitted in a backward propagation modeand is finally received at the radar receiver Such retransmit-ted power components from each of the interfaces received bythe radar receiver in a backward propagationmode are calledthe backward reflected power The transmitted power or thereflected power respectively through or from every interfaceduring either mode of propagation forward or backward ismultiplied by the power attenuation factor of the correspond-ing layer before entering into the next tissue layer

(i) Reflection Coefficient The characteristic behavior of theincident and reflected signals at every tissue interface of theplanar eleven-layer model (Figure 3) based on the impedancetransformation approach as a function of frequency is com-puted using MATLAB Considering the completely relaxedstate of the heart at the end of diastole the variation ofreflection coefficient of heart wall with frequency is plottedas shown in Figure 6 A five-point moving average is super-imposed for clear understanding

It is observed that the average reflection coefficient isas close as minus3 dB (approximately) over the whole band offrequency This means that about half of the electromagneticpower incident on the model is reflected back and theother half is transmitted into the body Moreover the reflec-tion coefficient value is negative at any frequency becausethe impedance offered by the human body is less than

6 Journal of Engineering

0

0 01 02 03 04 05 06 07 08

Sign

al at

tenu

atio

n (d

B)

Time (s)

minus60

minus50

minus40

minus30

minus20

minus10

(a)

0 01 02 03 04 05 06 07 08Time (s)

0

Sign

al at

tenu

atio

n (d

B)

minus90

minus80

minus70

minus60

minus50

minus40

minus30

minus20

minus10

(b)

0 01 02 03 04 05 06 07 08Time (s)

Sign

al at

tenu

atio

n (d

B)

minus28minus30minus32minus34minus36minus38minus40minus42minus44minus46

(c)

Figure 7 Variation of signal attenuation with time at (a) 01 GHz (b) 05 GHz and (c) 1 GHz respectively

the impedance of free space This implies that the reflectedpulses have an inverse relationship with respect to theincident pulses

(ii) Signal Attenuation The backward reflected power fromthe heart wall (interface-6) that is the heart-lung interface(119875minus

6119903)1015840 out of the total power input at the chest surface

(interface-1) 119875119894 is defined as the signal attenuation due to the

UWB pulse echo for the frequencies in the entire band of01 to 105 GHz and can be determined by using (8) as givenbelow The attenuation factor product and the transmissioncoefficient product can be evaluated by using (9) and (10)respectively

(119875minus

6119903)1015840

=1003816100381610038161003816Γ6

1003816100381610038161003816

2

times (attenuation factor product)2

times (transmission coefficient product)2 119875119894

(8)

whereattenuation factor product

= 119890minus21205722ℓ2119890minus21205723ℓ3119890minus21205724ℓ4119890minus21205725ℓ5119890minus21205726ℓ6

(9)

transmission coefficient product

= [(1 minus1003816100381610038161003816Γ1

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ2

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ3

1003816100381610038161003816

2

)

sdot (1 minus1003816100381610038161003816Γ4

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ5

1003816100381610038161003816

2

)]

(10)

The subscripts 2 3 4 5 and 6 refer to the layers suchas skin fat muscle cartilage and lung respectively for

the calculation of the attenuation factor product and thesubscripts 1 2 3 4 and 5 refer to skin-fat fat-muscle muscle-cartilage cartilage-lung and lung-heart interfaces respec-tively for the calculation of the transmission coefficientproduct Thus the signal power attenuation is calculated forsome typical frequencies in the band of 01 to 105 GHz using(8) through (10)

The model predicted average attenuation is minus98 dB at31 GHz which is in good agreement with the attenuation ofminus93 dB at this frequency as predicted by [2] but for a differentthorax model Similarly the model predicted attenuationis minus978 dB at 3GHz and is in good agreement with theattenuation of minus100 dB at this frequency as predicted by [4]

At different instants of time in the cardiac cycle heartassumes different dimensions In other words the dimen-sions of the layer representing heart are related to the dimen-sion of heart Therefore the variation of attenuation withdimension is directly related to the variation of the heartdimensions with time Hence the attenuation characteristicfor different dimensions is related to the heart movementFigures 7(a) through 7(c) represent the variation of atten-uation for typical frequencies of 01 05 and 1GHz withtime respectively and the time has been associated with thewidth of the heart (Figure 2) Thus the period between themaximum attenuations corresponds to the heart beat periodIn the case of 01 GHz the minimum attenuation occurs atthe heart dimension equal to 1004mm corresponding tothe instant of 03 seconds and the maximum attenuationtakes place at 1114mm at the end of diastole as depicted inFigure 7(a) The similar behavior is also observed at other

Journal of Engineering 7

0

01

03

05

15

25

31 4 5 6 7 8 9 10

f (GHz)

Max

imum

at

tenu

atio

n (d

B)

Max attenuationFive-point moving average

minus350

minus300

minus250

minus200

minus150

minus100

minus50

(a)

f (GHz)Min attenuationFive-point moving average

0

01

03

05

15

25

31 4 5 6 7 8 9 10

Min

imum

at

tenu

atio

n (d

B)

minus250

minus200

minus150

minus100

minus50

(b)

Figure 8Variations of (a)maximumand (b)minimumsignal attenuationwith frequency Superimposed five-pointmoving average is plotted

frequencies for example 05 GHz 1 GHz and so forth asshown in Figures 7(b) and 7(c) respectively

This model predicted attenuation is obtained separatelyfor every instantaneously changing dimension of heart dur-ing the cardiac cycle It is found that there is a maximumand a minimum value of attenuation corresponding to everyfrequency in the band of 01 to 105 GHz as shown in Figure 8Superimposed is the five-point moving average plot It isobserved that the points of maximum and minimum atten-uation shift with frequency as depicted in Figures 8(a) and8(b) respectively

From this it may be noted that there is periodic variationin attenuation of an active heart at a given frequency Theperiodicity of attenuation characteristics (period betweenmaximum attenuation and minimum attenuation) refers tothe heartbeat period Knowing the period ofmaximumatten-uation or minimum attenuation one will be able to decidethe health of the heart Lack of periodicity might indicatethe problem of an unhealthy heartThis attenuationmeasure-ment can be carried out on persons who are not accessibleunlike other methods using stethoscope electrocardiograph(ECG) and so forth

5 Conclusions

Electromagnetic response of the human tissue is highlyfrequency dependent Of all the body tissues encountered inthe path of propagation heart is the onlymoving element thatcan have a noticeable displacement and all others are staticTherefore in the wake of the study of propagation charac-teristics that is signal attenuation and reflection coefficientwe focused computation of these parameters with chang-ing dimensions of heart during a complete cardiac cycleThen the change of attenuation and the reflection coefficientcorresponding to the change of heart size during relax-ation-contraction-relaxation (one cardiac cycle) at differentinstants of time during the cardiac period was studied Thiscan provide good information about the state of a personrsquosheart whether healthy or unhealthy Any noticeable changeof attenuation shall indicate that the person is live while nochange of attenuation found in this way might lead to anunusual guess that the person might be dead

In this paper we have presented a one-dimensionalelectromagnetic model of human body and incorporated theelectromagnetic properties of significant body tissues beyondheart corresponding to all frequencies from 01 to 105 GHz toaccommodate the FCC defined UWBMoreover the analysisis performed for changes with time of heart dimension notfor a fixed heart dimension as in earlier models A studyof variation of signal attenuation due to the instantaneouschange of heart dimensions during a cardiac cycle can pro-vide reliable information about the health of heart This fea-ture of change of signal attenuationmay also be used to studythe performance of cardiac activity of persons buried underthe rubbles of the debris of a collapsed building personsbehind a wall and so forth

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] EM Staderini ldquoUWB radars inmedicinerdquo IEEE Aerospace andElectronic Systems Magazine vol 17 no 1 pp 13ndash18 2002

[2] G Varotto and E M Staderini ldquoOn the UWB medical radarsworking principlesrdquo International Journal of Ultra WidebandCommunications and Systems vol 2 no 2 pp 83ndash93 2011

[3] K N Sahu C D Naidu and K Jaya Sankar ldquoFrequency depen-dent planar electromagnetic modeling of human body andtheoretical study on attenuation for budget estimation of UWBradarrdquo The Global Journal of Researches in Engineering vol 14no 3 pp 35ndash44 2014

[4] M Cavagnaro E Pittella and S Pisa ldquoUWB pulse propagationinto human tissuesrdquo Physics inMedicine and Biology vol 58 no24 pp 8689ndash8707 2013

[5] January 2010 httpwwwsciencekidsconzpictureshuman-bodyheartdiagramhtml

[6] D G Gibson T A Traill and D J Brown ldquoChanges in leftventricular free wall thickness in patients with ischaemic heartdiseaserdquo British Heart Journal vol 39 no 12 pp 1312ndash1318 1977

[7] K Hergan A Schuster M Mair R Burger and M TopkerldquoNormal cardiac diameters in cine-MRI of the heartrdquo RoFoFortschritte auf dem Gebiete der Rontgenstrahlen und der Nuk-learmedizin vol 176 no 11 pp 1599ndash1606 2004 (German)

8 Journal of Engineering

[8] January 2010 httpwwwstanfordedugroupccm echocardiocgi-binmediawikiindexphpLeft ventricle size

[9] T A Traill D G Gibson and D J Brown ldquoStudy of left ven-tricular wall thickness and dimension changes using echocar-diographyrdquo British Heart Journal vol 40 no 2 pp 162ndash1691978

[10] S Kaul G LWismer T J Brady et al ldquoMeasurement of normalleft heart dimensions using optimally oriented MR imagesrdquoAmerican Journal of Roentgenology vol 146 no 1 pp 75ndash791986

[11] L E Hudsmith S E Petersen J M Francis M D Robson andS Neubauer ldquoNormal human left and right ventricular and leftatrial dimensions using steady state free precession magneticresonance imagingrdquo Journal of Cardiovascular Magnetic Reso-nance vol 7 no 5 pp 775ndash782 2005

[12] R F Rushmer and N Thal ldquoThe mechanics of ventricularcontraction a Cinefluorographic Studyrdquo Circulation vol 4 no2 pp 219ndash228 1951

[13] C Gabriel ldquoCompilation of the dielectric properties of bodytissues at RF and microwave frequenciesrdquo Report ALOE-TR-1996-0037 Occupational and Environmental Health Direc-torate Radio Frequency Radiation Division Brooks Air ForceBase San Antonio Tex USA 1996

[14] Institute forApplied Physics ldquoAn Internet Resource forTheCal-culation of The Dielectric Properties of Body Tissuesrdquo ItalianNational Research Council httpniremfifaccnrittissprop

[15] W H Hayt and J A Buck Engineering Electromagnetics TataMcGraw-Hill Mumbai India 7th edition 2006

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RotatingMachinery

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Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Shock and Vibration

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Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Electrical and Computer Engineering

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Advances inOptoElectronics

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Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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International Journal of

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Navigation and Observation

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DistributedSensor Networks

International Journal of

4 Journal of Engineering

Air

1000

Skin

15 96

Muscle

135

Cartilage

116

Lung

578

Heart Cartilage

116

Muscle

135

Fat

96

Skin

15

AirFat

(a)

Air

1000

Skin

15 96

Muscle

135

Cartilage

116

Lung

578

Heart Cartilage

116

Muscle

135

Fat

96

Skin

15

AirFat

(b)

Figure 3 Tissue structure for EM modeling of human body (a) forward propagation (b) backward propagation Figures in the diagramindicate the thickness of the tissue layers in millimeter

0

20

40

60

80

100

120

140

160

180

01 1 2 3 4 5 6 7 8 9 10 11

Rela

tive p

erm

ittiv

ity m

agni

tude

f (GHz)

SkinFatMuscleCartilage

Deflated lungInflated lungHeart

(a)

SkinFatMuscleCartilage

Deflated lungInflated lungHeart

0

2

4

6

8

10

12

14

01 1 2 3 4 5 6 7 8 9 10 11

Con

duct

ivity

(Sm

)

f (GHz)

(b)

Figure 4 Variation of (a) relative permittivity (b) conductivity of tissues with frequency

phase-shift constant magnitude of intrinsic impedance andwave velocity also increase with frequency

3 Analysis of UWB Pulse Propagation intothe Model

As biological tissues are lossy media from an electromagneticpoint of view they are characterized in terms of the propaga-tion parameters discussed in Section 22These characteristicparameters are highly frequency dependent The incidentreflected and transmitted powers at any interface of themultilayered thorax model (Figure 3) are the result of a netforward wave due to the multiple reflections taking place inthe previous interfaces and the reflected wave may be consid-ered as the effect of all themultiple reflections occurring at theboundary Therefore the net incident reflected and trans-mitted powers at all tissue interfaces are calculated at typicalfrequencies of the ultrawideband range from 01 to 105 GHz

using the following power relations given by (1) through (3)as described in [15]

Net incident power 119875+119894=

(119864+

1)2

21205781

(1)

Net reflected power 119875minus119903=

(Γ119864+

1)2

21205781

= |Γ|2(119864+

1)2

21205781

= |Γ|2

119875+

119894

(2)

Net transmitted power 119875+119905= (1 minus |Γ|

2

) 119875+

119894 (3)

where |Γ| is the reflection coefficient magnitude at an inter-face

In the event of the wave reflection from such multipleinterfaces the impedance transformation method considersthe complicated sequence of multiple reflections in everylayer as explained in [15] assuming the normal incidence

Journal of Engineering 5

n = 1 n = 2 n = 3

1205781 1205782 1205783 1205784

P+1i

P+1t

P+2i

P+2t

P+3i

P+3t

Pminus3r

Pminus2r

z = l2 + l3 z = l3 z = 0

120578in1 120578in2 120578in3 = 1205784

Z

Figure 5 Planar impedance transformationmodel for a three-inter-face four-layer case

of a plane wave on every interface A three-interface four-layer configuration of the planar impedance transformationmodel is as shown in Figure 5 Using the boundary conditionson either side of an interface the effective input impedanceoffered by all subsequent layers to the right of every interfacecan be computed as obtained in [15] The effective inputimpedance at the interfaces 119899 = 3 2 and 1 can be givenby (4) through (6) respectively Using the input impedancevalues calculated in this way the reflection coefficient canthen be calculated at every interface for example reflectioncoefficient at interface 1 can be as given by (7)

At interface 3 the effective input impedance is

120578in3 = 1205784 (4)

At interface 2 the effective input impedance is

120578in2 = 12057831205784cos12057331198973+ 1198951205783sin12057331198973

1205783cos12057331198973+ 1198951205784sin12057331198973

(5)

and at interface 1 the effective input impedance becomes

120578in1 = 1205782120578in2 cos12057321198972 + 1198951205782 sin120573211989721205782cos12057321198972+ 119895120578in2 sin12057321198972

(6)

Then reflection coefficient at interface 1 can be expressed as

Γ1=

120578in1 minus 1205781

120578in1 + 1205781 (7)

where 1205781 1205782 1205783 and 120578

4are the intrinsic impedances 120573

2and

1205733are the wave numbers of the respective layers 119897

2and 1198973are

the thickness values of layers 2 and 3 respectivelySimilarly considering the eleven-layered tissue system

model (Figure 3) the input impedance and the reflec-tion coefficient corresponding to every tissue interface areobtained using a MATLAB program

Thus in order to study the behavior of the backscatteredfield from a human body illuminated by the plane elec-tromagnetic waves from a radar transmitter we simplified

0

01

02

03

04

05 1

15 2

25 3

31

35 4

45 5

55 6

65 7

75 8

85 9

95 10

105

Refle

ctio

n co

effici

ent (

dB)

f (GHz)Reflection coefficient (dB)Five-point moving average

minus10

minus8

minus6

minus4

minus2

Figure 6 Reflection coefficient from heart at the end of diastole Afive-pointmoving average is superimposed for a clearer understand-ing

the problem by modeling the human body as a series ofbiological tissue layers of complex permittivity Knowingthe permittivity of the tissue materials and by utilizingthe basic principles of electromagnetic wave propagation inaccordancewith the physical processes the power received bythe radar receiver the reflection coefficients at every interfaceand signal power attenuation of the heart are determined

4 Results and Discussion

When the power carried by the radar wave is incident onany interface ldquo119899rdquo separating the two tissue mediums ldquo119899rdquo andldquo119899 + 1rdquo part of it is transmitted to the next layer in the sameforward direction known as the transmitted power and theremaining power is reflected into its previous layer in thebackward direction known as the reflected power compo-nent The amount of power reflected from every interfacekeeps getting retransmitted in a backward propagation modeand is finally received at the radar receiver Such retransmit-ted power components from each of the interfaces received bythe radar receiver in a backward propagationmode are calledthe backward reflected power The transmitted power or thereflected power respectively through or from every interfaceduring either mode of propagation forward or backward ismultiplied by the power attenuation factor of the correspond-ing layer before entering into the next tissue layer

(i) Reflection Coefficient The characteristic behavior of theincident and reflected signals at every tissue interface of theplanar eleven-layer model (Figure 3) based on the impedancetransformation approach as a function of frequency is com-puted using MATLAB Considering the completely relaxedstate of the heart at the end of diastole the variation ofreflection coefficient of heart wall with frequency is plottedas shown in Figure 6 A five-point moving average is super-imposed for clear understanding

It is observed that the average reflection coefficient isas close as minus3 dB (approximately) over the whole band offrequency This means that about half of the electromagneticpower incident on the model is reflected back and theother half is transmitted into the body Moreover the reflec-tion coefficient value is negative at any frequency becausethe impedance offered by the human body is less than

6 Journal of Engineering

0

0 01 02 03 04 05 06 07 08

Sign

al at

tenu

atio

n (d

B)

Time (s)

minus60

minus50

minus40

minus30

minus20

minus10

(a)

0 01 02 03 04 05 06 07 08Time (s)

0

Sign

al at

tenu

atio

n (d

B)

minus90

minus80

minus70

minus60

minus50

minus40

minus30

minus20

minus10

(b)

0 01 02 03 04 05 06 07 08Time (s)

Sign

al at

tenu

atio

n (d

B)

minus28minus30minus32minus34minus36minus38minus40minus42minus44minus46

(c)

Figure 7 Variation of signal attenuation with time at (a) 01 GHz (b) 05 GHz and (c) 1 GHz respectively

the impedance of free space This implies that the reflectedpulses have an inverse relationship with respect to theincident pulses

(ii) Signal Attenuation The backward reflected power fromthe heart wall (interface-6) that is the heart-lung interface(119875minus

6119903)1015840 out of the total power input at the chest surface

(interface-1) 119875119894 is defined as the signal attenuation due to the

UWB pulse echo for the frequencies in the entire band of01 to 105 GHz and can be determined by using (8) as givenbelow The attenuation factor product and the transmissioncoefficient product can be evaluated by using (9) and (10)respectively

(119875minus

6119903)1015840

=1003816100381610038161003816Γ6

1003816100381610038161003816

2

times (attenuation factor product)2

times (transmission coefficient product)2 119875119894

(8)

whereattenuation factor product

= 119890minus21205722ℓ2119890minus21205723ℓ3119890minus21205724ℓ4119890minus21205725ℓ5119890minus21205726ℓ6

(9)

transmission coefficient product

= [(1 minus1003816100381610038161003816Γ1

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ2

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ3

1003816100381610038161003816

2

)

sdot (1 minus1003816100381610038161003816Γ4

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ5

1003816100381610038161003816

2

)]

(10)

The subscripts 2 3 4 5 and 6 refer to the layers suchas skin fat muscle cartilage and lung respectively for

the calculation of the attenuation factor product and thesubscripts 1 2 3 4 and 5 refer to skin-fat fat-muscle muscle-cartilage cartilage-lung and lung-heart interfaces respec-tively for the calculation of the transmission coefficientproduct Thus the signal power attenuation is calculated forsome typical frequencies in the band of 01 to 105 GHz using(8) through (10)

The model predicted average attenuation is minus98 dB at31 GHz which is in good agreement with the attenuation ofminus93 dB at this frequency as predicted by [2] but for a differentthorax model Similarly the model predicted attenuationis minus978 dB at 3GHz and is in good agreement with theattenuation of minus100 dB at this frequency as predicted by [4]

At different instants of time in the cardiac cycle heartassumes different dimensions In other words the dimen-sions of the layer representing heart are related to the dimen-sion of heart Therefore the variation of attenuation withdimension is directly related to the variation of the heartdimensions with time Hence the attenuation characteristicfor different dimensions is related to the heart movementFigures 7(a) through 7(c) represent the variation of atten-uation for typical frequencies of 01 05 and 1GHz withtime respectively and the time has been associated with thewidth of the heart (Figure 2) Thus the period between themaximum attenuations corresponds to the heart beat periodIn the case of 01 GHz the minimum attenuation occurs atthe heart dimension equal to 1004mm corresponding tothe instant of 03 seconds and the maximum attenuationtakes place at 1114mm at the end of diastole as depicted inFigure 7(a) The similar behavior is also observed at other

Journal of Engineering 7

0

01

03

05

15

25

31 4 5 6 7 8 9 10

f (GHz)

Max

imum

at

tenu

atio

n (d

B)

Max attenuationFive-point moving average

minus350

minus300

minus250

minus200

minus150

minus100

minus50

(a)

f (GHz)Min attenuationFive-point moving average

0

01

03

05

15

25

31 4 5 6 7 8 9 10

Min

imum

at

tenu

atio

n (d

B)

minus250

minus200

minus150

minus100

minus50

(b)

Figure 8Variations of (a)maximumand (b)minimumsignal attenuationwith frequency Superimposed five-pointmoving average is plotted

frequencies for example 05 GHz 1 GHz and so forth asshown in Figures 7(b) and 7(c) respectively

This model predicted attenuation is obtained separatelyfor every instantaneously changing dimension of heart dur-ing the cardiac cycle It is found that there is a maximumand a minimum value of attenuation corresponding to everyfrequency in the band of 01 to 105 GHz as shown in Figure 8Superimposed is the five-point moving average plot It isobserved that the points of maximum and minimum atten-uation shift with frequency as depicted in Figures 8(a) and8(b) respectively

From this it may be noted that there is periodic variationin attenuation of an active heart at a given frequency Theperiodicity of attenuation characteristics (period betweenmaximum attenuation and minimum attenuation) refers tothe heartbeat period Knowing the period ofmaximumatten-uation or minimum attenuation one will be able to decidethe health of the heart Lack of periodicity might indicatethe problem of an unhealthy heartThis attenuationmeasure-ment can be carried out on persons who are not accessibleunlike other methods using stethoscope electrocardiograph(ECG) and so forth

5 Conclusions

Electromagnetic response of the human tissue is highlyfrequency dependent Of all the body tissues encountered inthe path of propagation heart is the onlymoving element thatcan have a noticeable displacement and all others are staticTherefore in the wake of the study of propagation charac-teristics that is signal attenuation and reflection coefficientwe focused computation of these parameters with chang-ing dimensions of heart during a complete cardiac cycleThen the change of attenuation and the reflection coefficientcorresponding to the change of heart size during relax-ation-contraction-relaxation (one cardiac cycle) at differentinstants of time during the cardiac period was studied Thiscan provide good information about the state of a personrsquosheart whether healthy or unhealthy Any noticeable changeof attenuation shall indicate that the person is live while nochange of attenuation found in this way might lead to anunusual guess that the person might be dead

In this paper we have presented a one-dimensionalelectromagnetic model of human body and incorporated theelectromagnetic properties of significant body tissues beyondheart corresponding to all frequencies from 01 to 105 GHz toaccommodate the FCC defined UWBMoreover the analysisis performed for changes with time of heart dimension notfor a fixed heart dimension as in earlier models A studyof variation of signal attenuation due to the instantaneouschange of heart dimensions during a cardiac cycle can pro-vide reliable information about the health of heart This fea-ture of change of signal attenuationmay also be used to studythe performance of cardiac activity of persons buried underthe rubbles of the debris of a collapsed building personsbehind a wall and so forth

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] EM Staderini ldquoUWB radars inmedicinerdquo IEEE Aerospace andElectronic Systems Magazine vol 17 no 1 pp 13ndash18 2002

[2] G Varotto and E M Staderini ldquoOn the UWB medical radarsworking principlesrdquo International Journal of Ultra WidebandCommunications and Systems vol 2 no 2 pp 83ndash93 2011

[3] K N Sahu C D Naidu and K Jaya Sankar ldquoFrequency depen-dent planar electromagnetic modeling of human body andtheoretical study on attenuation for budget estimation of UWBradarrdquo The Global Journal of Researches in Engineering vol 14no 3 pp 35ndash44 2014

[4] M Cavagnaro E Pittella and S Pisa ldquoUWB pulse propagationinto human tissuesrdquo Physics inMedicine and Biology vol 58 no24 pp 8689ndash8707 2013

[5] January 2010 httpwwwsciencekidsconzpictureshuman-bodyheartdiagramhtml

[6] D G Gibson T A Traill and D J Brown ldquoChanges in leftventricular free wall thickness in patients with ischaemic heartdiseaserdquo British Heart Journal vol 39 no 12 pp 1312ndash1318 1977

[7] K Hergan A Schuster M Mair R Burger and M TopkerldquoNormal cardiac diameters in cine-MRI of the heartrdquo RoFoFortschritte auf dem Gebiete der Rontgenstrahlen und der Nuk-learmedizin vol 176 no 11 pp 1599ndash1606 2004 (German)

8 Journal of Engineering

[8] January 2010 httpwwwstanfordedugroupccm echocardiocgi-binmediawikiindexphpLeft ventricle size

[9] T A Traill D G Gibson and D J Brown ldquoStudy of left ven-tricular wall thickness and dimension changes using echocar-diographyrdquo British Heart Journal vol 40 no 2 pp 162ndash1691978

[10] S Kaul G LWismer T J Brady et al ldquoMeasurement of normalleft heart dimensions using optimally oriented MR imagesrdquoAmerican Journal of Roentgenology vol 146 no 1 pp 75ndash791986

[11] L E Hudsmith S E Petersen J M Francis M D Robson andS Neubauer ldquoNormal human left and right ventricular and leftatrial dimensions using steady state free precession magneticresonance imagingrdquo Journal of Cardiovascular Magnetic Reso-nance vol 7 no 5 pp 775ndash782 2005

[12] R F Rushmer and N Thal ldquoThe mechanics of ventricularcontraction a Cinefluorographic Studyrdquo Circulation vol 4 no2 pp 219ndash228 1951

[13] C Gabriel ldquoCompilation of the dielectric properties of bodytissues at RF and microwave frequenciesrdquo Report ALOE-TR-1996-0037 Occupational and Environmental Health Direc-torate Radio Frequency Radiation Division Brooks Air ForceBase San Antonio Tex USA 1996

[14] Institute forApplied Physics ldquoAn Internet Resource forTheCal-culation of The Dielectric Properties of Body Tissuesrdquo ItalianNational Research Council httpniremfifaccnrittissprop

[15] W H Hayt and J A Buck Engineering Electromagnetics TataMcGraw-Hill Mumbai India 7th edition 2006

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Engineering 5

n = 1 n = 2 n = 3

1205781 1205782 1205783 1205784

P+1i

P+1t

P+2i

P+2t

P+3i

P+3t

Pminus3r

Pminus2r

z = l2 + l3 z = l3 z = 0

120578in1 120578in2 120578in3 = 1205784

Z

Figure 5 Planar impedance transformationmodel for a three-inter-face four-layer case

of a plane wave on every interface A three-interface four-layer configuration of the planar impedance transformationmodel is as shown in Figure 5 Using the boundary conditionson either side of an interface the effective input impedanceoffered by all subsequent layers to the right of every interfacecan be computed as obtained in [15] The effective inputimpedance at the interfaces 119899 = 3 2 and 1 can be givenby (4) through (6) respectively Using the input impedancevalues calculated in this way the reflection coefficient canthen be calculated at every interface for example reflectioncoefficient at interface 1 can be as given by (7)

At interface 3 the effective input impedance is

120578in3 = 1205784 (4)

At interface 2 the effective input impedance is

120578in2 = 12057831205784cos12057331198973+ 1198951205783sin12057331198973

1205783cos12057331198973+ 1198951205784sin12057331198973

(5)

and at interface 1 the effective input impedance becomes

120578in1 = 1205782120578in2 cos12057321198972 + 1198951205782 sin120573211989721205782cos12057321198972+ 119895120578in2 sin12057321198972

(6)

Then reflection coefficient at interface 1 can be expressed as

Γ1=

120578in1 minus 1205781

120578in1 + 1205781 (7)

where 1205781 1205782 1205783 and 120578

4are the intrinsic impedances 120573

2and

1205733are the wave numbers of the respective layers 119897

2and 1198973are

the thickness values of layers 2 and 3 respectivelySimilarly considering the eleven-layered tissue system

model (Figure 3) the input impedance and the reflec-tion coefficient corresponding to every tissue interface areobtained using a MATLAB program

Thus in order to study the behavior of the backscatteredfield from a human body illuminated by the plane elec-tromagnetic waves from a radar transmitter we simplified

0

01

02

03

04

05 1

15 2

25 3

31

35 4

45 5

55 6

65 7

75 8

85 9

95 10

105

Refle

ctio

n co

effici

ent (

dB)

f (GHz)Reflection coefficient (dB)Five-point moving average

minus10

minus8

minus6

minus4

minus2

Figure 6 Reflection coefficient from heart at the end of diastole Afive-pointmoving average is superimposed for a clearer understand-ing

the problem by modeling the human body as a series ofbiological tissue layers of complex permittivity Knowingthe permittivity of the tissue materials and by utilizingthe basic principles of electromagnetic wave propagation inaccordancewith the physical processes the power received bythe radar receiver the reflection coefficients at every interfaceand signal power attenuation of the heart are determined

4 Results and Discussion

When the power carried by the radar wave is incident onany interface ldquo119899rdquo separating the two tissue mediums ldquo119899rdquo andldquo119899 + 1rdquo part of it is transmitted to the next layer in the sameforward direction known as the transmitted power and theremaining power is reflected into its previous layer in thebackward direction known as the reflected power compo-nent The amount of power reflected from every interfacekeeps getting retransmitted in a backward propagation modeand is finally received at the radar receiver Such retransmit-ted power components from each of the interfaces received bythe radar receiver in a backward propagationmode are calledthe backward reflected power The transmitted power or thereflected power respectively through or from every interfaceduring either mode of propagation forward or backward ismultiplied by the power attenuation factor of the correspond-ing layer before entering into the next tissue layer

(i) Reflection Coefficient The characteristic behavior of theincident and reflected signals at every tissue interface of theplanar eleven-layer model (Figure 3) based on the impedancetransformation approach as a function of frequency is com-puted using MATLAB Considering the completely relaxedstate of the heart at the end of diastole the variation ofreflection coefficient of heart wall with frequency is plottedas shown in Figure 6 A five-point moving average is super-imposed for clear understanding

It is observed that the average reflection coefficient isas close as minus3 dB (approximately) over the whole band offrequency This means that about half of the electromagneticpower incident on the model is reflected back and theother half is transmitted into the body Moreover the reflec-tion coefficient value is negative at any frequency becausethe impedance offered by the human body is less than

6 Journal of Engineering

0

0 01 02 03 04 05 06 07 08

Sign

al at

tenu

atio

n (d

B)

Time (s)

minus60

minus50

minus40

minus30

minus20

minus10

(a)

0 01 02 03 04 05 06 07 08Time (s)

0

Sign

al at

tenu

atio

n (d

B)

minus90

minus80

minus70

minus60

minus50

minus40

minus30

minus20

minus10

(b)

0 01 02 03 04 05 06 07 08Time (s)

Sign

al at

tenu

atio

n (d

B)

minus28minus30minus32minus34minus36minus38minus40minus42minus44minus46

(c)

Figure 7 Variation of signal attenuation with time at (a) 01 GHz (b) 05 GHz and (c) 1 GHz respectively

the impedance of free space This implies that the reflectedpulses have an inverse relationship with respect to theincident pulses

(ii) Signal Attenuation The backward reflected power fromthe heart wall (interface-6) that is the heart-lung interface(119875minus

6119903)1015840 out of the total power input at the chest surface

(interface-1) 119875119894 is defined as the signal attenuation due to the

UWB pulse echo for the frequencies in the entire band of01 to 105 GHz and can be determined by using (8) as givenbelow The attenuation factor product and the transmissioncoefficient product can be evaluated by using (9) and (10)respectively

(119875minus

6119903)1015840

=1003816100381610038161003816Γ6

1003816100381610038161003816

2

times (attenuation factor product)2

times (transmission coefficient product)2 119875119894

(8)

whereattenuation factor product

= 119890minus21205722ℓ2119890minus21205723ℓ3119890minus21205724ℓ4119890minus21205725ℓ5119890minus21205726ℓ6

(9)

transmission coefficient product

= [(1 minus1003816100381610038161003816Γ1

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ2

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ3

1003816100381610038161003816

2

)

sdot (1 minus1003816100381610038161003816Γ4

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ5

1003816100381610038161003816

2

)]

(10)

The subscripts 2 3 4 5 and 6 refer to the layers suchas skin fat muscle cartilage and lung respectively for

the calculation of the attenuation factor product and thesubscripts 1 2 3 4 and 5 refer to skin-fat fat-muscle muscle-cartilage cartilage-lung and lung-heart interfaces respec-tively for the calculation of the transmission coefficientproduct Thus the signal power attenuation is calculated forsome typical frequencies in the band of 01 to 105 GHz using(8) through (10)

The model predicted average attenuation is minus98 dB at31 GHz which is in good agreement with the attenuation ofminus93 dB at this frequency as predicted by [2] but for a differentthorax model Similarly the model predicted attenuationis minus978 dB at 3GHz and is in good agreement with theattenuation of minus100 dB at this frequency as predicted by [4]

At different instants of time in the cardiac cycle heartassumes different dimensions In other words the dimen-sions of the layer representing heart are related to the dimen-sion of heart Therefore the variation of attenuation withdimension is directly related to the variation of the heartdimensions with time Hence the attenuation characteristicfor different dimensions is related to the heart movementFigures 7(a) through 7(c) represent the variation of atten-uation for typical frequencies of 01 05 and 1GHz withtime respectively and the time has been associated with thewidth of the heart (Figure 2) Thus the period between themaximum attenuations corresponds to the heart beat periodIn the case of 01 GHz the minimum attenuation occurs atthe heart dimension equal to 1004mm corresponding tothe instant of 03 seconds and the maximum attenuationtakes place at 1114mm at the end of diastole as depicted inFigure 7(a) The similar behavior is also observed at other

Journal of Engineering 7

0

01

03

05

15

25

31 4 5 6 7 8 9 10

f (GHz)

Max

imum

at

tenu

atio

n (d

B)

Max attenuationFive-point moving average

minus350

minus300

minus250

minus200

minus150

minus100

minus50

(a)

f (GHz)Min attenuationFive-point moving average

0

01

03

05

15

25

31 4 5 6 7 8 9 10

Min

imum

at

tenu

atio

n (d

B)

minus250

minus200

minus150

minus100

minus50

(b)

Figure 8Variations of (a)maximumand (b)minimumsignal attenuationwith frequency Superimposed five-pointmoving average is plotted

frequencies for example 05 GHz 1 GHz and so forth asshown in Figures 7(b) and 7(c) respectively

This model predicted attenuation is obtained separatelyfor every instantaneously changing dimension of heart dur-ing the cardiac cycle It is found that there is a maximumand a minimum value of attenuation corresponding to everyfrequency in the band of 01 to 105 GHz as shown in Figure 8Superimposed is the five-point moving average plot It isobserved that the points of maximum and minimum atten-uation shift with frequency as depicted in Figures 8(a) and8(b) respectively

From this it may be noted that there is periodic variationin attenuation of an active heart at a given frequency Theperiodicity of attenuation characteristics (period betweenmaximum attenuation and minimum attenuation) refers tothe heartbeat period Knowing the period ofmaximumatten-uation or minimum attenuation one will be able to decidethe health of the heart Lack of periodicity might indicatethe problem of an unhealthy heartThis attenuationmeasure-ment can be carried out on persons who are not accessibleunlike other methods using stethoscope electrocardiograph(ECG) and so forth

5 Conclusions

Electromagnetic response of the human tissue is highlyfrequency dependent Of all the body tissues encountered inthe path of propagation heart is the onlymoving element thatcan have a noticeable displacement and all others are staticTherefore in the wake of the study of propagation charac-teristics that is signal attenuation and reflection coefficientwe focused computation of these parameters with chang-ing dimensions of heart during a complete cardiac cycleThen the change of attenuation and the reflection coefficientcorresponding to the change of heart size during relax-ation-contraction-relaxation (one cardiac cycle) at differentinstants of time during the cardiac period was studied Thiscan provide good information about the state of a personrsquosheart whether healthy or unhealthy Any noticeable changeof attenuation shall indicate that the person is live while nochange of attenuation found in this way might lead to anunusual guess that the person might be dead

In this paper we have presented a one-dimensionalelectromagnetic model of human body and incorporated theelectromagnetic properties of significant body tissues beyondheart corresponding to all frequencies from 01 to 105 GHz toaccommodate the FCC defined UWBMoreover the analysisis performed for changes with time of heart dimension notfor a fixed heart dimension as in earlier models A studyof variation of signal attenuation due to the instantaneouschange of heart dimensions during a cardiac cycle can pro-vide reliable information about the health of heart This fea-ture of change of signal attenuationmay also be used to studythe performance of cardiac activity of persons buried underthe rubbles of the debris of a collapsed building personsbehind a wall and so forth

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] EM Staderini ldquoUWB radars inmedicinerdquo IEEE Aerospace andElectronic Systems Magazine vol 17 no 1 pp 13ndash18 2002

[2] G Varotto and E M Staderini ldquoOn the UWB medical radarsworking principlesrdquo International Journal of Ultra WidebandCommunications and Systems vol 2 no 2 pp 83ndash93 2011

[3] K N Sahu C D Naidu and K Jaya Sankar ldquoFrequency depen-dent planar electromagnetic modeling of human body andtheoretical study on attenuation for budget estimation of UWBradarrdquo The Global Journal of Researches in Engineering vol 14no 3 pp 35ndash44 2014

[4] M Cavagnaro E Pittella and S Pisa ldquoUWB pulse propagationinto human tissuesrdquo Physics inMedicine and Biology vol 58 no24 pp 8689ndash8707 2013

[5] January 2010 httpwwwsciencekidsconzpictureshuman-bodyheartdiagramhtml

[6] D G Gibson T A Traill and D J Brown ldquoChanges in leftventricular free wall thickness in patients with ischaemic heartdiseaserdquo British Heart Journal vol 39 no 12 pp 1312ndash1318 1977

[7] K Hergan A Schuster M Mair R Burger and M TopkerldquoNormal cardiac diameters in cine-MRI of the heartrdquo RoFoFortschritte auf dem Gebiete der Rontgenstrahlen und der Nuk-learmedizin vol 176 no 11 pp 1599ndash1606 2004 (German)

8 Journal of Engineering

[8] January 2010 httpwwwstanfordedugroupccm echocardiocgi-binmediawikiindexphpLeft ventricle size

[9] T A Traill D G Gibson and D J Brown ldquoStudy of left ven-tricular wall thickness and dimension changes using echocar-diographyrdquo British Heart Journal vol 40 no 2 pp 162ndash1691978

[10] S Kaul G LWismer T J Brady et al ldquoMeasurement of normalleft heart dimensions using optimally oriented MR imagesrdquoAmerican Journal of Roentgenology vol 146 no 1 pp 75ndash791986

[11] L E Hudsmith S E Petersen J M Francis M D Robson andS Neubauer ldquoNormal human left and right ventricular and leftatrial dimensions using steady state free precession magneticresonance imagingrdquo Journal of Cardiovascular Magnetic Reso-nance vol 7 no 5 pp 775ndash782 2005

[12] R F Rushmer and N Thal ldquoThe mechanics of ventricularcontraction a Cinefluorographic Studyrdquo Circulation vol 4 no2 pp 219ndash228 1951

[13] C Gabriel ldquoCompilation of the dielectric properties of bodytissues at RF and microwave frequenciesrdquo Report ALOE-TR-1996-0037 Occupational and Environmental Health Direc-torate Radio Frequency Radiation Division Brooks Air ForceBase San Antonio Tex USA 1996

[14] Institute forApplied Physics ldquoAn Internet Resource forTheCal-culation of The Dielectric Properties of Body Tissuesrdquo ItalianNational Research Council httpniremfifaccnrittissprop

[15] W H Hayt and J A Buck Engineering Electromagnetics TataMcGraw-Hill Mumbai India 7th edition 2006

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

6 Journal of Engineering

0

0 01 02 03 04 05 06 07 08

Sign

al at

tenu

atio

n (d

B)

Time (s)

minus60

minus50

minus40

minus30

minus20

minus10

(a)

0 01 02 03 04 05 06 07 08Time (s)

0

Sign

al at

tenu

atio

n (d

B)

minus90

minus80

minus70

minus60

minus50

minus40

minus30

minus20

minus10

(b)

0 01 02 03 04 05 06 07 08Time (s)

Sign

al at

tenu

atio

n (d

B)

minus28minus30minus32minus34minus36minus38minus40minus42minus44minus46

(c)

Figure 7 Variation of signal attenuation with time at (a) 01 GHz (b) 05 GHz and (c) 1 GHz respectively

the impedance of free space This implies that the reflectedpulses have an inverse relationship with respect to theincident pulses

(ii) Signal Attenuation The backward reflected power fromthe heart wall (interface-6) that is the heart-lung interface(119875minus

6119903)1015840 out of the total power input at the chest surface

(interface-1) 119875119894 is defined as the signal attenuation due to the

UWB pulse echo for the frequencies in the entire band of01 to 105 GHz and can be determined by using (8) as givenbelow The attenuation factor product and the transmissioncoefficient product can be evaluated by using (9) and (10)respectively

(119875minus

6119903)1015840

=1003816100381610038161003816Γ6

1003816100381610038161003816

2

times (attenuation factor product)2

times (transmission coefficient product)2 119875119894

(8)

whereattenuation factor product

= 119890minus21205722ℓ2119890minus21205723ℓ3119890minus21205724ℓ4119890minus21205725ℓ5119890minus21205726ℓ6

(9)

transmission coefficient product

= [(1 minus1003816100381610038161003816Γ1

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ2

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ3

1003816100381610038161003816

2

)

sdot (1 minus1003816100381610038161003816Γ4

1003816100381610038161003816

2

) (1 minus1003816100381610038161003816Γ5

1003816100381610038161003816

2

)]

(10)

The subscripts 2 3 4 5 and 6 refer to the layers suchas skin fat muscle cartilage and lung respectively for

the calculation of the attenuation factor product and thesubscripts 1 2 3 4 and 5 refer to skin-fat fat-muscle muscle-cartilage cartilage-lung and lung-heart interfaces respec-tively for the calculation of the transmission coefficientproduct Thus the signal power attenuation is calculated forsome typical frequencies in the band of 01 to 105 GHz using(8) through (10)

The model predicted average attenuation is minus98 dB at31 GHz which is in good agreement with the attenuation ofminus93 dB at this frequency as predicted by [2] but for a differentthorax model Similarly the model predicted attenuationis minus978 dB at 3GHz and is in good agreement with theattenuation of minus100 dB at this frequency as predicted by [4]

At different instants of time in the cardiac cycle heartassumes different dimensions In other words the dimen-sions of the layer representing heart are related to the dimen-sion of heart Therefore the variation of attenuation withdimension is directly related to the variation of the heartdimensions with time Hence the attenuation characteristicfor different dimensions is related to the heart movementFigures 7(a) through 7(c) represent the variation of atten-uation for typical frequencies of 01 05 and 1GHz withtime respectively and the time has been associated with thewidth of the heart (Figure 2) Thus the period between themaximum attenuations corresponds to the heart beat periodIn the case of 01 GHz the minimum attenuation occurs atthe heart dimension equal to 1004mm corresponding tothe instant of 03 seconds and the maximum attenuationtakes place at 1114mm at the end of diastole as depicted inFigure 7(a) The similar behavior is also observed at other

Journal of Engineering 7

0

01

03

05

15

25

31 4 5 6 7 8 9 10

f (GHz)

Max

imum

at

tenu

atio

n (d

B)

Max attenuationFive-point moving average

minus350

minus300

minus250

minus200

minus150

minus100

minus50

(a)

f (GHz)Min attenuationFive-point moving average

0

01

03

05

15

25

31 4 5 6 7 8 9 10

Min

imum

at

tenu

atio

n (d

B)

minus250

minus200

minus150

minus100

minus50

(b)

Figure 8Variations of (a)maximumand (b)minimumsignal attenuationwith frequency Superimposed five-pointmoving average is plotted

frequencies for example 05 GHz 1 GHz and so forth asshown in Figures 7(b) and 7(c) respectively

This model predicted attenuation is obtained separatelyfor every instantaneously changing dimension of heart dur-ing the cardiac cycle It is found that there is a maximumand a minimum value of attenuation corresponding to everyfrequency in the band of 01 to 105 GHz as shown in Figure 8Superimposed is the five-point moving average plot It isobserved that the points of maximum and minimum atten-uation shift with frequency as depicted in Figures 8(a) and8(b) respectively

From this it may be noted that there is periodic variationin attenuation of an active heart at a given frequency Theperiodicity of attenuation characteristics (period betweenmaximum attenuation and minimum attenuation) refers tothe heartbeat period Knowing the period ofmaximumatten-uation or minimum attenuation one will be able to decidethe health of the heart Lack of periodicity might indicatethe problem of an unhealthy heartThis attenuationmeasure-ment can be carried out on persons who are not accessibleunlike other methods using stethoscope electrocardiograph(ECG) and so forth

5 Conclusions

Electromagnetic response of the human tissue is highlyfrequency dependent Of all the body tissues encountered inthe path of propagation heart is the onlymoving element thatcan have a noticeable displacement and all others are staticTherefore in the wake of the study of propagation charac-teristics that is signal attenuation and reflection coefficientwe focused computation of these parameters with chang-ing dimensions of heart during a complete cardiac cycleThen the change of attenuation and the reflection coefficientcorresponding to the change of heart size during relax-ation-contraction-relaxation (one cardiac cycle) at differentinstants of time during the cardiac period was studied Thiscan provide good information about the state of a personrsquosheart whether healthy or unhealthy Any noticeable changeof attenuation shall indicate that the person is live while nochange of attenuation found in this way might lead to anunusual guess that the person might be dead

In this paper we have presented a one-dimensionalelectromagnetic model of human body and incorporated theelectromagnetic properties of significant body tissues beyondheart corresponding to all frequencies from 01 to 105 GHz toaccommodate the FCC defined UWBMoreover the analysisis performed for changes with time of heart dimension notfor a fixed heart dimension as in earlier models A studyof variation of signal attenuation due to the instantaneouschange of heart dimensions during a cardiac cycle can pro-vide reliable information about the health of heart This fea-ture of change of signal attenuationmay also be used to studythe performance of cardiac activity of persons buried underthe rubbles of the debris of a collapsed building personsbehind a wall and so forth

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] EM Staderini ldquoUWB radars inmedicinerdquo IEEE Aerospace andElectronic Systems Magazine vol 17 no 1 pp 13ndash18 2002

[2] G Varotto and E M Staderini ldquoOn the UWB medical radarsworking principlesrdquo International Journal of Ultra WidebandCommunications and Systems vol 2 no 2 pp 83ndash93 2011

[3] K N Sahu C D Naidu and K Jaya Sankar ldquoFrequency depen-dent planar electromagnetic modeling of human body andtheoretical study on attenuation for budget estimation of UWBradarrdquo The Global Journal of Researches in Engineering vol 14no 3 pp 35ndash44 2014

[4] M Cavagnaro E Pittella and S Pisa ldquoUWB pulse propagationinto human tissuesrdquo Physics inMedicine and Biology vol 58 no24 pp 8689ndash8707 2013

[5] January 2010 httpwwwsciencekidsconzpictureshuman-bodyheartdiagramhtml

[6] D G Gibson T A Traill and D J Brown ldquoChanges in leftventricular free wall thickness in patients with ischaemic heartdiseaserdquo British Heart Journal vol 39 no 12 pp 1312ndash1318 1977

[7] K Hergan A Schuster M Mair R Burger and M TopkerldquoNormal cardiac diameters in cine-MRI of the heartrdquo RoFoFortschritte auf dem Gebiete der Rontgenstrahlen und der Nuk-learmedizin vol 176 no 11 pp 1599ndash1606 2004 (German)

8 Journal of Engineering

[8] January 2010 httpwwwstanfordedugroupccm echocardiocgi-binmediawikiindexphpLeft ventricle size

[9] T A Traill D G Gibson and D J Brown ldquoStudy of left ven-tricular wall thickness and dimension changes using echocar-diographyrdquo British Heart Journal vol 40 no 2 pp 162ndash1691978

[10] S Kaul G LWismer T J Brady et al ldquoMeasurement of normalleft heart dimensions using optimally oriented MR imagesrdquoAmerican Journal of Roentgenology vol 146 no 1 pp 75ndash791986

[11] L E Hudsmith S E Petersen J M Francis M D Robson andS Neubauer ldquoNormal human left and right ventricular and leftatrial dimensions using steady state free precession magneticresonance imagingrdquo Journal of Cardiovascular Magnetic Reso-nance vol 7 no 5 pp 775ndash782 2005

[12] R F Rushmer and N Thal ldquoThe mechanics of ventricularcontraction a Cinefluorographic Studyrdquo Circulation vol 4 no2 pp 219ndash228 1951

[13] C Gabriel ldquoCompilation of the dielectric properties of bodytissues at RF and microwave frequenciesrdquo Report ALOE-TR-1996-0037 Occupational and Environmental Health Direc-torate Radio Frequency Radiation Division Brooks Air ForceBase San Antonio Tex USA 1996

[14] Institute forApplied Physics ldquoAn Internet Resource forTheCal-culation of The Dielectric Properties of Body Tissuesrdquo ItalianNational Research Council httpniremfifaccnrittissprop

[15] W H Hayt and J A Buck Engineering Electromagnetics TataMcGraw-Hill Mumbai India 7th edition 2006

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Engineering 7

0

01

03

05

15

25

31 4 5 6 7 8 9 10

f (GHz)

Max

imum

at

tenu

atio

n (d

B)

Max attenuationFive-point moving average

minus350

minus300

minus250

minus200

minus150

minus100

minus50

(a)

f (GHz)Min attenuationFive-point moving average

0

01

03

05

15

25

31 4 5 6 7 8 9 10

Min

imum

at

tenu

atio

n (d

B)

minus250

minus200

minus150

minus100

minus50

(b)

Figure 8Variations of (a)maximumand (b)minimumsignal attenuationwith frequency Superimposed five-pointmoving average is plotted

frequencies for example 05 GHz 1 GHz and so forth asshown in Figures 7(b) and 7(c) respectively

This model predicted attenuation is obtained separatelyfor every instantaneously changing dimension of heart dur-ing the cardiac cycle It is found that there is a maximumand a minimum value of attenuation corresponding to everyfrequency in the band of 01 to 105 GHz as shown in Figure 8Superimposed is the five-point moving average plot It isobserved that the points of maximum and minimum atten-uation shift with frequency as depicted in Figures 8(a) and8(b) respectively

From this it may be noted that there is periodic variationin attenuation of an active heart at a given frequency Theperiodicity of attenuation characteristics (period betweenmaximum attenuation and minimum attenuation) refers tothe heartbeat period Knowing the period ofmaximumatten-uation or minimum attenuation one will be able to decidethe health of the heart Lack of periodicity might indicatethe problem of an unhealthy heartThis attenuationmeasure-ment can be carried out on persons who are not accessibleunlike other methods using stethoscope electrocardiograph(ECG) and so forth

5 Conclusions

Electromagnetic response of the human tissue is highlyfrequency dependent Of all the body tissues encountered inthe path of propagation heart is the onlymoving element thatcan have a noticeable displacement and all others are staticTherefore in the wake of the study of propagation charac-teristics that is signal attenuation and reflection coefficientwe focused computation of these parameters with chang-ing dimensions of heart during a complete cardiac cycleThen the change of attenuation and the reflection coefficientcorresponding to the change of heart size during relax-ation-contraction-relaxation (one cardiac cycle) at differentinstants of time during the cardiac period was studied Thiscan provide good information about the state of a personrsquosheart whether healthy or unhealthy Any noticeable changeof attenuation shall indicate that the person is live while nochange of attenuation found in this way might lead to anunusual guess that the person might be dead

In this paper we have presented a one-dimensionalelectromagnetic model of human body and incorporated theelectromagnetic properties of significant body tissues beyondheart corresponding to all frequencies from 01 to 105 GHz toaccommodate the FCC defined UWBMoreover the analysisis performed for changes with time of heart dimension notfor a fixed heart dimension as in earlier models A studyof variation of signal attenuation due to the instantaneouschange of heart dimensions during a cardiac cycle can pro-vide reliable information about the health of heart This fea-ture of change of signal attenuationmay also be used to studythe performance of cardiac activity of persons buried underthe rubbles of the debris of a collapsed building personsbehind a wall and so forth

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] EM Staderini ldquoUWB radars inmedicinerdquo IEEE Aerospace andElectronic Systems Magazine vol 17 no 1 pp 13ndash18 2002

[2] G Varotto and E M Staderini ldquoOn the UWB medical radarsworking principlesrdquo International Journal of Ultra WidebandCommunications and Systems vol 2 no 2 pp 83ndash93 2011

[3] K N Sahu C D Naidu and K Jaya Sankar ldquoFrequency depen-dent planar electromagnetic modeling of human body andtheoretical study on attenuation for budget estimation of UWBradarrdquo The Global Journal of Researches in Engineering vol 14no 3 pp 35ndash44 2014

[4] M Cavagnaro E Pittella and S Pisa ldquoUWB pulse propagationinto human tissuesrdquo Physics inMedicine and Biology vol 58 no24 pp 8689ndash8707 2013

[5] January 2010 httpwwwsciencekidsconzpictureshuman-bodyheartdiagramhtml

[6] D G Gibson T A Traill and D J Brown ldquoChanges in leftventricular free wall thickness in patients with ischaemic heartdiseaserdquo British Heart Journal vol 39 no 12 pp 1312ndash1318 1977

[7] K Hergan A Schuster M Mair R Burger and M TopkerldquoNormal cardiac diameters in cine-MRI of the heartrdquo RoFoFortschritte auf dem Gebiete der Rontgenstrahlen und der Nuk-learmedizin vol 176 no 11 pp 1599ndash1606 2004 (German)

8 Journal of Engineering

[8] January 2010 httpwwwstanfordedugroupccm echocardiocgi-binmediawikiindexphpLeft ventricle size

[9] T A Traill D G Gibson and D J Brown ldquoStudy of left ven-tricular wall thickness and dimension changes using echocar-diographyrdquo British Heart Journal vol 40 no 2 pp 162ndash1691978

[10] S Kaul G LWismer T J Brady et al ldquoMeasurement of normalleft heart dimensions using optimally oriented MR imagesrdquoAmerican Journal of Roentgenology vol 146 no 1 pp 75ndash791986

[11] L E Hudsmith S E Petersen J M Francis M D Robson andS Neubauer ldquoNormal human left and right ventricular and leftatrial dimensions using steady state free precession magneticresonance imagingrdquo Journal of Cardiovascular Magnetic Reso-nance vol 7 no 5 pp 775ndash782 2005

[12] R F Rushmer and N Thal ldquoThe mechanics of ventricularcontraction a Cinefluorographic Studyrdquo Circulation vol 4 no2 pp 219ndash228 1951

[13] C Gabriel ldquoCompilation of the dielectric properties of bodytissues at RF and microwave frequenciesrdquo Report ALOE-TR-1996-0037 Occupational and Environmental Health Direc-torate Radio Frequency Radiation Division Brooks Air ForceBase San Antonio Tex USA 1996

[14] Institute forApplied Physics ldquoAn Internet Resource forTheCal-culation of The Dielectric Properties of Body Tissuesrdquo ItalianNational Research Council httpniremfifaccnrittissprop

[15] W H Hayt and J A Buck Engineering Electromagnetics TataMcGraw-Hill Mumbai India 7th edition 2006

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

8 Journal of Engineering

[8] January 2010 httpwwwstanfordedugroupccm echocardiocgi-binmediawikiindexphpLeft ventricle size

[9] T A Traill D G Gibson and D J Brown ldquoStudy of left ven-tricular wall thickness and dimension changes using echocar-diographyrdquo British Heart Journal vol 40 no 2 pp 162ndash1691978

[10] S Kaul G LWismer T J Brady et al ldquoMeasurement of normalleft heart dimensions using optimally oriented MR imagesrdquoAmerican Journal of Roentgenology vol 146 no 1 pp 75ndash791986

[11] L E Hudsmith S E Petersen J M Francis M D Robson andS Neubauer ldquoNormal human left and right ventricular and leftatrial dimensions using steady state free precession magneticresonance imagingrdquo Journal of Cardiovascular Magnetic Reso-nance vol 7 no 5 pp 775ndash782 2005

[12] R F Rushmer and N Thal ldquoThe mechanics of ventricularcontraction a Cinefluorographic Studyrdquo Circulation vol 4 no2 pp 219ndash228 1951

[13] C Gabriel ldquoCompilation of the dielectric properties of bodytissues at RF and microwave frequenciesrdquo Report ALOE-TR-1996-0037 Occupational and Environmental Health Direc-torate Radio Frequency Radiation Division Brooks Air ForceBase San Antonio Tex USA 1996

[14] Institute forApplied Physics ldquoAn Internet Resource forTheCal-culation of The Dielectric Properties of Body Tissuesrdquo ItalianNational Research Council httpniremfifaccnrittissprop

[15] W H Hayt and J A Buck Engineering Electromagnetics TataMcGraw-Hill Mumbai India 7th edition 2006

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of