non-ionizing electromagnetic radiation effects on...

NON-IONIZING ELECTROMAGNETIC RADIATION EFFECTS ON THE

ACTION POTENTIAL IN HUMAN ARM ELECTRICAL MODEL

ADIB BIN OTHMAN

A thesis submitted in

fulfillment of the requirement for the award of the

Degree of Master of Electrical Engineering

Faculty of Electrical and Electronic Engineering

Universiti Tun Hussein Onn Malaysia

SEPTEMBER 2015

v

ABSTRACT

The common use of Global System for Mobile Communications (GSM) phones has

initiated research regarding the possible biological hazardous effects of exposure to

electromagnetic (EM) radiation. Therefore, it is essential to study the extent of

interaction of GSM phone radiation towards action potentials (AP) in nerve fibres. In

order to investigate the effects of GSM phone radiation towards human arm AP,

human brain-arm nerve fibres were modeled as wire-type transmission lines; two

wires and one wire. Both models with and without interference source from the

radiation were simulated and the output waveforms have been analysed to detect any

existence of interference. The interference source value was obtained by finding

electric and magnetic fields in nerve layer of simulated human arm model that been

exposed by GSM phone radiation. Robotic arm experiment setup was developed to

measure effects of the radiation towards the electrical signal of robotic arm as

indirect comparison to AP. Simulation results show the radiation is capable of

disturbing the normal AP by introducing bursting spikes on it when distance of the

phone from the human arm model is 9 mm with phone radiation power as low as

0.02 W. Furthermore, large nerve fibre radius with huge exposure area to the EM

waves also adds on to the effect of radiation on the AP. The altered AP might disturb

the normal functions of human arm and hence lead to potential health hazard. The

robotic arm has shown displacement from 0.2 cm to 1 cm from the original location

when placing an object to its required place when there are active GSM phones near

the robotic setup. The measured electrical signal of the robotic arm shows brief

distortion in its signal with distortion magnitude up to 0.58 V. This distortion

observation is quite similar to the AP when there is induced source in the nerve fibre

models. In conclusion, there are significance effects of EM radiation towards the AP

in human nervous system.

vi

ABSTRAK

Penggunaan telefon mudah alih yang beroperasi di dalam mod GSM telah banyak

mencetuskan penyelidikan mengenai kesan biologi berbahaya yang berkemungkinan

terjadi kepada hidupan akibat pendedahan kepada radiasi elektromagnetik. Oleh itu,

adalah penting untuk mengkaji sejauh mana interaksi radiasi telefon GSM terhadap

potensi tindakan dalam gentian saraf. Untuk menyiasat kesan-kesan radiasi telefon

GSM kepada potensi tindakan di dalam lengan manusia, gentian saraf dari otak ke

lengan telah dimodelkan sebagai talian penghantaran berwayar dua dan berwayar

satu. Kedua-dua model dengan dan tanpa gangguan daripada sumber radiasi telah

disimulasikan dan gelombang keluaran telah dianalisis untuk mengesan sebarang

kewujudan gangguan. Nilai sumber gangguan telah diperolehi dengan mencari

medan elektrik dan medan magnet dalam lapisan saraf dari simulasi model lengan

manusia yang telah terdedah dengan radiasi telefon GSM. Ujikaji menggunakan

lengan robotik telah dibangunkan untuk mengukur kesan radiasi ke arah isyarat

elektrik di dalam lengan robotik sebagai perbandingan tidak langsung kepada potensi

tindakan. Keputusan simulasi menunjukkan radiasi mampu menganggu potensi

tindakan di dalam saraf dengan mewujudkan pacak gangguan di atasnya apabila

jarak telefon dari model tangan manusia ialah 9 mm dengan kuasa radiasi telefon

tersebut serendah 0.02 W. Perubahan terhadap potensi tindakan mungkin

mengganggu fungsi normal lengan manusia dan dengan itu membawa kepada potensi

kesihatan yang merbahaya. Lengan robotik telah menunjukkan anjakan di dalam

lingkungan 0.2 cm ke 1 cm daripada tempat asalnya semasa ingin meletakkan objek

apabila terdapat telefon GSM yang aktif berhampiran dengan lengan robotik. Isyarat

elektrik yang diukur dari lengan robotik menunjukkan gangguan di dalam isyarat

dengan magnitud gangguan sehingga 0.58 V. Pengamatan daripada gangguan ini

adalah sama seperti apa yang berlaku kepada potensi tindakan di dalam model

gentian saraf apabila terdapat sumber radiasi berdekatan. Secara kesimpulannya,

terdapat kesan signifikan dari radiasi elektomagnetik kepada potensi tindakan di

dalam sistem saraf manusia.

vii

CONTENTS

TITLE i

STUDENT DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

CONTENTS vii

LIST OF TABLES ix

LIST OF FIGURES x

LIST OF SYMBOLS AND ABBREVIATIONS xxii

LIST OF APPENDICES xxiii

CHAPTER 1 INTRODUCTION 1

1.1 Background studies 2

1.2 Problem statement 4

1.3 Aim of research 4

1.4 Objectives of research 4

1.5 Scopes of research 5

1.6 Thesis organization 5

CHAPTER 2 LITERATURE REVIEW 7

2.1 Relationship between EM radiation and health

hazards 8

2.2 Neurological electrophysiology effects of EM

radiation 9

2.3 Physiology of human nervous system 10

2.4 Neuron electrical circuits and action potential

mathematical models 15

2.5 Simple susceptibility model 26

2.6 OWI-535 robotic arm edge overview 28

viii

2.7 GSM mobile phone overview 30

2.8 Chapter 2 summary 32

CHAPTER 3 METHODOLOGY 33

3.1 Human arm modeling 34

3.2 Brain-arm nerve fibre modeling 39

3.3 EM radiation interference in brain-arm nerve

fibres modeling 45

3.4 Robotic arm experiments 47

3.5 Chapter 3 summary 54

CHAPTER 4 RESULTS AND DISCUSSION 56

4.1 Radiation fields penetration process into nerve

fibre of human brain-arm 57

4.2 Electric and magnetic fields in nerve layer of

human arm model 63

4.3 AP in nerve fibre of human brain-arm TL model 78

4.4 FFT analysis on AP results 97

4.5 Robotic arm movement results 106

4.6 Review of achievement and contribution 116

CHAPTER 5 CONCLUSIONS 118

5.1 Conclusions 118

5.2 Future recommendations 119

REFERENCES 120

APPENDIX 127

ix

LISTS OF TABLES

Table 3.1: Human arm organs and tissue properties .................................................. 35

Table 3.2: Images of phone orientation ..................................................................... 37

Table 4.1: E, H and W directions for different phone orientations ............................ 61

Table 4.2: Possible induced sources for all phone orientation ................................... 63

Table 4.3: Incident electric field, transmitted electric field and shielding

effectiveness, SE for various phone orientations ...................................... 66

Table 4.4: Electric field and magnetic field in nerve layer for 1 W and

0.02 W radiated powers for various phone orientations ............................ 68

Table 4.5: Phone locations along the human arm model with 0o phone

orientation .................................................................................................. 71

Table 4.6: Phone distances from the human arm model with 0o phone

orientation .................................................................................................. 73

Table 4.7: SAR results from simulation..................................................................... 75

Table 4.8: Summary of defined and calculated parameters ....................................... 96

Table 4.9: Radiation magnitude on AP for both one wire and two wire

TL models ................................................................................................ 105

Table 4.10: Received voltage from Nokia phone at different orientations .............. 107

Table 4.11: Received voltage from Samsung phone at different

orientations ............................................................................................ 107

Table 4.12: Received voltage from U-com phone at different orientations ............. 108

Table 4.13: Received voltage from Sony Ericsson phone at different

orientations ............................................................................................ 108

x

LISTS OF FIGURES

Figure 1.1: Source of EM radiation [5] 2

Figure 1.2: Human nervous system [10] 3

Figure 2.1: Action potential and its phases [35] 12

Figure 2.2: Motor control organization for muscle movement [36] 13

Figure 2.3: Descending tracts for muscle motor neurons [36] 14

Figure 2.4: Hodgkin and Huxley nerve fibre electrical model [11] 15

Figure 2.5: Voltage-gated K+ channel in closed (on left) and opened

(on right) states [36] 17

Figure 2.6: Voltage-gated Na+ channel in closed (on left), opened

(at middle) and inactive (on left) states [36] 18

Figure 2.7: Morris-Lecar electrical circuit model [12] 19

Figure 2.8: Isolated bursting AP produced by Hindmarsh and Rose

model [13] 22

Figure 2.9: Comparison of AP in rat's motor cortex and Izhikevich's

model [15] 26

Figure 2.10: Incident EM wave converted to interference sources in

simple susceptibility model [54] 27

Figure 2.11: Voltage source due to electric field convert into current

source [54] 28

Figure 2.12: OWI-535 robotic arm edge joints [55] 29

Figure 2.13: Dimensions of OWI-535 robotic arm edge [55] 29

Figure 2.14: Radiation from GSM phone towards human body part 30

Figure 2.15: GMSK modulated signal [61] 31

Figure 3.1: Simplest form of human arm in axial view 34

Figure 3.2: Human arm model with a GSM phone in vertical orientation 35

Figure 3.3: Human arm model replace with air 36

Figure 3.4: Nerve fibre of two wires and one wire lossless TL models in

PSPICE 41

Figure 3.5: Typical two wires lossless TL model 41

Figure 3.6: Typical one wire lossless TL model 42

Figure 3.7: Anatomy of human brain-arm nerve fibre [9, 36] 44

Figure 3.8: Actual nerve fibres tracts of two wires and one wire TL

models 45

Figure 3.9: Actual nerve fibres tracts with induced radiation current

sources 45

xi

Figure 3.10: Actual nerve fibres tracts with induced radiation voltage

sources 46

Figure 3.11: Creation of DC signal by using LabVIEW software 48

Figure 3.12: DC source produced by LabVIEW 48

Figure 3.13: NI 9263 module in NI cDAQ-9178 49

Figure 3.14: Robotic arm experiment setup with GSM phones at 0o

phone orientation 50

Figure 3.15: Radiated wave in parallel with the monopole antenna 51

Figure 3.16: Radiated wave not in parallel with the monopole antenna 51

Figure 3.17: Setup for determining the propagated wave position from

mobile phone 52

Figure 3.18: Mobile phones model 53

Figure 3.19: Methodology flowchart 54

Figure 4.1: Radiated electric and magnetic field from a monopole

antenna [78] 57

Figure 4.2: Surface current for 0o to 180

o phase 57

Figure 4.3: Surface current for 180o to 360

o phase 58

Figure 4.4: Magnetic field for 0o to 180

o phase 58

Figure 4.5: Magnetic field for 180o to 360

o phase 58

Figure 4.6: Electric field for 0o to 180

o phase 59

Figure 4.7: Electric field for 180o to 360

o phase 59

Figure 4.8: Nerve axial view [79] 62

Figure 4.9: Incident electric field with GSM phone at 0o phone

orientation 63

Figure 4.10: Transmitted electric field with GSM phone at 0o phone

orientation 64

Figure 4.11: Incident electric field with GSM phone at 45o phone

orientation 65

Figure 4.12: Transmitted electric field with GSM phone at 45o phone

orientation 65

Figure 4.13: Electric field in nerve layer with GSM phone at 0o phone

orientation 66

Figure 4.14: Magnetic field in nerve layer with GSM phone at 0o

phone orientation 67

Figure 4.15: Shielding effectiveness comparison for various phone

orientations 69

Figure 4.16: Electric fields comparison for various phone orientations 70

Figure 4.17: Magnetic fields comparison for various phone orientations 70

Figure 4.18: Electric fields comparison for different phone location

along the human arm at 0o phone orientation 72

Figure 4.19: Electric fields comparison for different phone location

along the human arm at 90o phone orientation 72

Figure 4.20: Electric fields comparison for different phone distance

from the human arm at 0o phone orientation 74

xii

Figure 4.21: Electric fields comparison for different phone distance

from the human arm at 135o phone orientation 74

Figure 4.22: Electric fields comparison for different phone radiation

power at 0o phone orientation 77

Figure 4.23: Electric fields comparison for different phone radiation

power at 270o phone orientation 77

Figure 4.24: Interference of an induced current source on one wire

TL model 78

Figure 4.25: Interference of an induced current source on two wires

TL model 79

Figure 4.26: Interference of an induced voltage source on one wire

TL model 79

Figure 4.27: Interference of an induced voltage source on two wires

TL model 80


TL model with varied phone orientations 81








TL model with varied phone distance 84








TL model with varied phone radiation power 86








TL model with varied nerve fibre radius 89





xiii




TL model with varied h 91


TL model with varied h 91


TL model with varied s 92


TL model with varied s 92

Figure 4.48: Original AP produced by one unit of Hodgkin and Huxley

model 94

Figure 4.49: AP produced by one unit of Hodgkin and Huxley model

that interfered by induced voltage source 94

Figure 4.50: AP produced by one unit of Hodgkin and Huxley model

that interfered by induced current source 95

Figure 4.51: FFT of AP in one wire TL model affected by induced

current source with phone orientation at 0o 98






voltage source with phone orientation at 90o 100






current source with phone distance at 9 mm 102






voltage source with phone distance at 9 mm 103





Figure 4.63: First reading of received voltage from Nokia phone at

0o orientation 106

Figure 4.64: Second reading of received voltage from Nokia phone at

0o orientation 106

xiv

Figure 4.65: Third reading of received voltage from Nokia phone at

0o orientation 107

Figure 4.66: Location of antenna at each mobile phone 109

Figure 4.67(a): Match box placement without radiation source 110

Figure 4.67(b): Match box placement with phones at 0o orientation 110

Figure 4.67(c): Match box placement with phones at 45o orientation 110

Figure 4.67(d): Match box placement with phones at 90o orientation 110

Figure 4.67(e): Match box placement with phones at 135o orientation 110

Figure 4.67(f): Match box placement with phones at 180o orientation 110

Figure 4.67(g): Match box placement with phones at 225o orientation 111

Figure 4.67(h): Match box placement with phones at 270o orientation 111

Figure 4.67(i): Match box placement with phones at 315o orientation 111

Figure 4.68: Robotic arm signal in unmovable state with appearance

of phone at 0o 112


of phone at 45o 113


of phone at 180o 113



Figure 4.72: Robotic arm signal in movable state with appearance

of phone at 0o 114

Figure 4.73: Robotic arm signal in movable state with appearance


Figure B - A: Incident electric field with GSM phone at various phone

orientations ....................................................................................... 130

Figure B - B: Transmitted electric field with GSM phone at various

phone orientations ............................................................................ 130

Figure C - A: Electric field comparison for different phone location

along the human arm at 45 degree phone orientation ...................... 131

Figure C - B: Electric field comparison for different phone location

along the human arm at 135 degree phone orientation .................... 131

Figure C - C: Electric field comparison for different phone location


Figure C - D: Electric field comparison for different phone location


Figure C - E: Electric field comparison for different phone location


Figure C - F: Electric field comparison for different phone location


Figure D - A: Electric field comparison for different phone distance

from the human arm at 45 degree phone orientation ........................ 133

Figure D - B: Electric field comparison for different phone distance

from the human arm at 90 degree phone orientation ........................ 133

xv

Figure D - C: Electric field comparison for different phone distance

from the human arm at 180 degree phone orientation ...................... 133

Figure D - D: Electric field comparison for different phone distance


Figure D - E: Electric field comparison for different phone distance


Figure D - F: Electric field comparison for different phone distance


Figure E - A: Electric field comparison for different phone radiation

power at 45 degree phone orientation ................................................. 135

Figure E - B: Electric field comparison for different phone radiation

power at 90 degree phone orientation ................................................. 135

Figure E - C: Electric field comparison for different phone radiation

power at 135 degree phone orientation ............................................... 135

Figure E - D: Electric field comparison for different phone radiation


Figure E - E: Electric field comparison for different phone radiation


Figure E - F: Electric field comparison for different phone radiation


Figure G - A: FFT of AP in one wire TL model affected by induced

current source with phone radiation power at 0.02 W ..................... 178

Figure G - B: FFT of AP in one wire TL model affected by induced

current source with phone radiation power at 0.2 W ....................... 178

Figure G - C: FFT of AP in one wire TL model affected by induced

current source with phone radiation power at 1 W .......................... 179

Figure G - D: FFT of AP in one wire TL model affected by induced

voltage source with phone radiation power at 0.02 W ..................... 179

Figure G - E: FFT of AP in one wire TL model affected by induced

voltage source with phone radiation power at 0.2 W ....................... 180

Figure G - F: FFT of AP in one wire TL model affected by induced

voltage source with phone radiation power at 1 W .......................... 180

Figure G - G: FFT of AP in one wire TL model affected by induced

current source with 10 μm nerve fibre radius ................................... 181

Figure G - H: FFT of AP in one wire TL model affected by induced

current source with 5 μm nerve fibre radius ..................................... 181

Figure G - I: FFT of AP in one wire TL model affected by induced

current source with 2.5 μm nerve fibre radius .................................. 182

Figure G - J: FFT of AP in one wire TL model affected by induced

voltage source with 10 μm nerve fibre radius .................................. 182

Figure G - K: FFT of AP in one wire TL model affected by induced

voltage source with 5 μm nerve fibre radius .................................... 183

Figure G - L: FFT of AP in one wire TL model affected by induced

voltage source with 2.5 μm nerve fibre radius ................................. 183

xvi

Figure G - M: FFT of AP in one wire TL model affected by induced

current source with 10.01 μm h factor.............................................. 184

Figure G - N: FFT of AP in one wire TL model affected by induced

current source with 10.007 μm h factor............................................ 184

Figure G - O: FFT of AP in one wire TL model affected by induced

current source with 10.004 μm h factor............................................ 185

Figure G - P: FFT of AP in one wire TL model affected by induced

voltage source with 10.01 μm h factor ............................................. 185

Figure G - Q: FFT of AP in one wire TL model affected by induced

voltage source with 10.007 μm h factor ........................................... 186

Figure G - R: FFT of AP in one wire TL model affected by induced

voltage source with 10.004 μm h factor ........................................... 186

Figure G - S: FFT of AP in two wires TL model affected by induced

current source with phone orientation at 0o ...................................... 187

Figure G - T: FFT of AP in two wires TL model affected by induced

current source with phone orientation at 45o .................................... 187

Figure G - U: FFT of AP in two wires TL model affected by induced

current source with phone orientation at 135o .................................. 188

Figure G - V: FFT of AP in two wires TL model affected by induced

voltage source with phone orientation at 90o ................................... 188

Figure G - W: FFT of AP in two wires TL model affected by induced

voltage source with phone orientation at 45o ................................... 189

Figure G - X: FFT of AP in two wires TL model affected by induced

voltage source with phone orientation at 135o ................................. 189

Figure G - Y: FFT of AP in two wires TL model affected by induced

current source with phone distance at 9 mm .................................... 190

Figure G - Z: FFT of AP in two wires TL model affected by induced

current source with phone distance at 56 mm .................................. 190

Figure G - AA: FFT of AP in two wires TL model affected by induced

current source with phone distance at 1000 mm .............................. 191

Figure G - BB: FFT of AP in two wires TL model affected by induced

voltage source with phone distance at 9 mm .................................... 191

Figure G - CC: FFT of AP in two wires TL model affected by induced

voltage source with phone distance at 56 mm .................................. 192

Figure G - DD: FFT of AP in two wires TL model affected by induced

voltage source with phone distance at 1000 mm .............................. 192

Figure G - EE: FFT of AP in two wires TL model affected by induced

current source with phone radiation power at 0.02 W ..................... 193

Figure G - FF: FFT of AP in two wires TL model affected by induced

current source with phone radiation power at 0.2 W ....................... 193

Figure G - GG: FFT of AP in two wires TL model affected by induced

current source with phone radiation power at 1 W .......................... 194

Figure G - HH: FFT of AP in two wires TL model affected by induced

voltage source with phone radiation power at 0.02 W ..................... 194

xvii

Figure G - II: FFT of AP in two wires TL model affected by induced

voltage source with phone radiation power at 0.2 W ....................... 195

Figure G - JJ: FFT of AP in two wires TL model affected by induced

voltage source with phone radiation power at 1 W .......................... 195

Figure G - KK: FFT of AP in two wires TL model affected by induced

current source with 10 μm nerve fibre radius ................................... 196

Figure G - LL: FFT of AP in two wires TL model affected by induced

current source with 5 μm nerve fibre radius ..................................... 196

Figure G - MM: FFT of AP in two wires TL model affected by induced

current source with 2.5 μm nerve fibre radius .................................. 197

Figure G - NN: FFT of AP in two wires TL model affected by induced

voltage source with 10 μm nerve fibre radius .................................. 197

Figure G - OO: FFT of AP in two wires TL model affected by induced

voltage source with 5 μm nerve fibre radius .................................... 198

Figure G - PP: FFT of AP in two wires TL model affected by induced

voltage source with 2.5 μm nerve fibre radius ................................. 198

Figure G - QQ: FFT of AP in two wires TL model affected by induced

current source with 50 μm s factor ................................................... 199

Figure G - RR: FFT of AP in two wires TL model affected by induced


Figure G - SS: FFT of AP in two wires TL model affected by induced


Figure G - TT: FFT of AP in two wires TL model affected by induced

voltage source with 50 μm s factor................................................... 200

Figure G - UU: FFT of AP in two wires TL model affected by induced


Figure G - VV: FFT of AP in two wires TL model affected by induced


Figure H - A: First reading of received voltage from Nokia phone at

45 degree orientation ........................................................................ 202

Figure H - B: Second reading of received voltage from Nokia phone at


Figure H - C: Third reading of received voltage from Nokia phone at


Figure H - D: First reading of received voltage from Nokia phone at


Figure H - E: Second reading of received voltage from Nokia phone at


Figure H - F: Third reading of received voltage from Nokia phone at


Figure H - G: First reading of received voltage from Nokia phone at

135 degree orientation ...................................................................... 204

Figure H - H: Second reading of received voltage from Nokia phone at

135 degree orientation ...................................................................... 204

xviii

Figure H - I: Third reading of received voltage from Nokia phone

at 135 degree orientation .................................................................. 204

Figure H - J: First reading of received voltage from Nokia phone


Figure H - K: Second reading of received voltage from Nokia phone


Figure H - L: Third reading of received voltage from Nokia phone


Figure H - M: First reading of received voltage from Nokia phone


Figure H - N: Second reading of received voltage from Nokia phone


Figure H - O: Third reading of received voltage from Nokia phone


Figure H - P: First reading of received voltage from Nokia phone


Figure H - Q: Second reading of received voltage from Nokia phone


Figure H - R: Third reading of received voltage from Nokia phone


Figure H - S: First reading of received voltage from Nokia phone


Figure H - T: Second reading of received voltage from Nokia phone


Figure H - U: Third reading of received voltage from Nokia phone


Figure H - V: First reading of received voltage from Samsung phone

at 0 degree orientation ...................................................................... 209

Figure H - W: Second reading of received voltage from Samsung phone


Figure H - X: Third reading of received voltage from Samsung phone


Figure H - Y: First reading of received voltage from Samsung phone

at 45 degree orientation .................................................................... 210

Figure H - Z: Second reading of received voltage from Samsung phone


Figure H - AA: Third reading of received voltage from Samsung phone


Figure H - BB: First reading of received voltage from Samsung phone


Figure H - CC: Second reading of received voltage from Samsung phone


Figure H - DD: Third reading of received voltage from Samsung phone


xix

Figure H - EE: First reading of received voltage from Samsung phone

at 135 degree orientation ................................................................ 212

Figure H - FF: Second reading of received voltage from Samsung phone


Figure H - GG: Third reading of received voltage from Samsung phone


Figure H - HH: First reading of received voltage from Samsung phone


Figure H - II: Second reading of received voltage from Samsung phone


Figure H - JJ: Third reading of received voltage from Samsung phone


Figure H - KK: First reading of received voltage from Samsung phone


Figure H - LL: Second reading of received voltage from Samsung phone


Figure H - MM: Third reading of received voltage from Samsung phone


Figure H - NN: First reading of received voltage from Samsung phone


Figure H - OO: Second reading of received voltage from Samsung phone


Figure H - PP: Third reading of received voltage from Samsung phone


Figure H - QQ: First reading of received voltage from Samsung phone


Figure H - RR: Second reading of received voltage from Samsung phone


Figure H - SS: Third reading of received voltage from Samsung phone


Figure H - TT: First reading of received voltage from U-com phone


Figure H - UU: Second reading of received voltage from U-com phone


Figure H - VV: Third reading of received voltage from U-com phone


Figure H - WW: First reading of received voltage from U-com phone


Figure H - XX: Second reading of received voltage from U-com phone


Figure H - YY: Third reading of received voltage from U-com phone


Figure H - ZZ: First reading of received voltage from U-com phone


xx

Figure H - AAA: Second reading of received voltage from U-com phone

at 90 degree orientation ............................................................... 219

Figure H - BBB: Third reading of received voltage from U-com phone

at 90 degree orientation ............................................................... 219

Figure H - CCC: First reading of received voltage from U-com phone

at 135 degree orientation ............................................................. 220

Figure H - DDD: Second reading of received voltage from U-com phone


Figure H - EEE: Third reading of received voltage from U-com phone


Figure H - FFF: First reading of received voltage from U-com phone


Figure H - GGG: Second reading of received voltage from U-com phone


Figure H - HHH: Third reading of received voltage from U-com phone


Figure H - III: First reading of received voltage from U-com phone


Figure H - JJJ: Second reading of received voltage from U-com phone


Figure H - KKK: Third reading of received voltage from U-com phone


Figure H - LLL: First reading of received voltage from U-com phone


Figure H - MMM: Second reading of received voltage from U-com phone


Figure H - NNN: Third reading of received voltage from U-com phone


Figure H - OOO: First reading of received voltage from U-com phone


Figure H - PPP: Second reading of received voltage from U-com phone


Figure H - QQQ: Third reading of received voltage from U-com phone


Figure H - RRR: First reading of received voltage from Sony Ericsson

phone at 0 degree orientation ....................................................... 225

Figure H - SSS: Second reading of received voltage from Sony Ericsson


Figure H - TTT: Third reading of received voltage from Sony Ericsson


Figure H - UUU: First reading of received voltage from Sony Ericsson

phone at 45 degree orientation ..................................................... 226

Figure H - VVV: Second reading of received voltage from Sony Ericsson


xxi

Figure H - WWW: Third reading of received voltage from Sony Ericsson


Figure H - XXX: First reading of received voltage from Sony Ericsson


Figure H - YYY: Second reading of received voltage from Sony Ericsson


Figure H - ZZZ: Third reading of received voltage from Sony Ericsson


Figure H - AAAA: First reading of received voltage from Sony Ericsson

phone at 135 degree orientation .............................................. 228

Figure H - BBBB: Second reading of received voltage from Sony Ericsson


Figure H - CCCC: Third reading of received voltage from Sony Ericsson


Figure H - DDDD: First reading of received voltage from Sony Ericsson


Figure H - EEEE: Second reading of received voltage from Sony Ericsson


Figure H - FFFF: Third reading of received voltage from Sony Ericsson


Figure H - GGGG: First reading of received voltage from Sony Ericsson


Figure H - HHHH: Second reading of received voltage from Sony Ericsson


Figure H - IIII: Third reading of received voltage from Sony Ericsson


Figure H - JJJJ: First reading of received voltage from Sony Ericsson


Figure H - KKKK: Second reading of received voltage from Sony Ericsson


Figure H - LLLL: Third reading of received voltage from Sony Ericsson


Figure H - MMMM: First reading of received voltage from Sony Ericsson


Figure H - NNNN: Second reading of received voltage from Sony Ericsson


Figure H - OOOO: Third reading of received voltage from Sony Ericsson


xxii

LISTS OF SYMBOLS AND ABBREVATIONS

GSM - Global System for Mobile Communication

AP - Action Potential

TL - Transmission Line

EM - Electromagnetic

WHO - World Health Organization

EMF - Electromagnetic Field

ICNIRP - International Committee on Non-Ionizing Radiation Protection

IEEE - Institute of Electrical and Electronic Engineering

IEGMP - Independent Expert Group on Mobile Phones

AHP - Afterhyperpolarization

Na - Sodium

K - Potassium

ICF - Intracellular Fluid

ECF - Extracellular Fluid

Ca - Calcium

DC - Direct Current

emf - Electromagnetic Force

PCB - Printed Circuit Board

TDMA - Time Division Multiple Access

FDMA - Frequency Division Multiple Access

GMSK - Gaussian Minimum Shift Keying

CST - Computer Simulation Technology

PIFA - Planar Inverted F Antenna

CNS - Central Nervous System

PNS - Peripheral Nervous System

SE - Shielding Effectiveness

SAR - Specific Absorption Rate

FFT - Fast Fourier Transform

xxiii

LISTS OF APPENDICES

APPENDIX TITLE PAGE

A

MATLAB programming for shielding effectiveness…………..…..127

B Incident and transmitted electric fields for various phone

orientations……...…………...………………………………….....130

C Electric field results base on relationship between phone

orientations and phone location along the human arm 131

D Electric field results base on relationship between phone

orientations and phone distance from the human arm 133

E Electric field results base on relationship between phone

orientations and phone radiation power 135

F

Summary of defined and calculated parameters for

actual nerve fibre tracts circuits considering all parameter

variations…….………….. 137

G FFT results for one wire and two wires transmission line

models considering all parameter variations………..…………… 178

H Received voltage from different phones at various phone

orientations………………………………………………...…… 202

1

CHAPTER 1

INTRODUCTION

The effects of non-ionizing electromagnetic (EM) pollution on humans have been

studied for more than 50 years. The World Health Organization (WHO), through its

International Electromagnetic Field (EMF) Project, has conducted a series of in-

depth international reviews of the scientific literature on the biological and health

effects of exposure to electromagnetic fields. WHO website (www.who.int) contains

more than 3400 entries of which more than 1800 are relevant to health effects of EM

exposure. The studies conclude their findings based on evidence collated from

epidemiological, animal or in vitro studies.

In depth studies showed that, human nervous system is the electrical system

of human body. Neurons are the fundamental unit of the nervous system that carries

electrical pulses known as action potentials (AP). This AP assists the communication

and coordination functions of the nervous system with other systems in human body.

Lots of research in neurons and AP has produced biophysical electrical equivalent

circuits as well as mathematical models representing the behaviour of AP

inside neurons.

2

1.1 Background studies

Non-ionizing radiation is electromagnetic radiation that does not alter atomic

structure [1]. It is well accepted that human exposure to non-ionizing EM radiation

can have multiple effects on the body. Many studies [2, 3, 4] over the years have

positively reported thermal or heating effect and non-thermal effects that cause from

non-ionizing EM radiation. Whilst thermal effect can have adverse health effects due

to heating of the tissue, the consequences of non-thermal effects such as cell

interaction, neuro-stimulation and behavioural changes are still subjected to

differences of opinion amongst researchers, governments and industries.

How the EM energy interacts with the body depends on a number of factors

some of which include frequency, signal strength, exposure time, modulation, and a

person’s natural immune system. The relationship between these and other factors

makes it extremely difficult to determine exact cause effect relationships. This

complexity just adds to the controversy over the carcinogenic effects of EM radiation

from high tension power, computer monitors, mobile phones, base stations and other

equipment as shown in Figure 1.1 which are in common use today.

Figure 1.1: Source of EM radiation [5]

The International Committee on Non-Ionizing Radiation Protection

(ICNIRP), which was established in 1992, published guidelines [6] limiting exposure

to time-varying electric, magnetic and electromagnetic fields to an acceptable level

3

to avoid adverse health effect. Other standards are based on work by IEEE and other

national and international commissions [7, 8]. The guidelines maybe insignificant for

certain attributes of humans because some people do not experience the symptoms

associated with non-ionizing EM radiation as much as others. However, long-term

exposure that does not lead to immediate symptoms can still result in cumulative

physiological effects that may ultimately cause serious disease. Every person is

affected by EM, but some people are more sensitive, less resilient and therefore more

susceptible to health problems.

Our body is a combination of many systems that work simultaneously and

always working relatedly to each other. The human body consists of systems such as

muscular system, cardiovascular system, endocrine system, immune system, nervous

system and few others of them to be name. The nervous system acts as a command

system that coordinate systems in human body, so they can work in an appropriate

manner [9]. A very special part in the nervous system that is so powerful that it

controls other systems in human body is the brain. In support with the spine and also

a very large mesh network so called nerve fibre make the system to become very

sophisticated system in the field of anatomy and physiology.

In electrical engineering point of view, the nerve fibre network is suitable to

be converted into electrical circuits in order to make observation and analyses easier

and results obtain can be relate logically to the real situation. As referring to Figure

1.2, the brain is likely to function as a source which produces the AP, nerve fibre as a

transmission line (TL) circuit that transmit the AP to trigger a movement on finger

muscle which act as a load.

Figure 1.2: Human nervous system [10]

brain

nerve

fibre

finger

muscle

4

The statement in previous sentence is supported by studies from many

researches. Hodgkin and Huxley [11] and Morris and Lecar [12] are researchers

whose responsible in converting nerve fibre to a TL circuit. Hindmarsh and Rose

[13], Wilson [14] and Izhikevich [15] have produced mathematical models that

functioning as similar to brain neural network which produced continuous AP

throughout the nervous system. Details about work been done by these

researchers will be explained briefly in literature review.

1.2 Problem statement

Unawareness of long term pollution from non-ionizing EM radiation to the human

body is a critical issue nowadays. Either thermal effect or non-thermal effect can

bring threats to humans and even any living organism. The EM radiation can easily

penetrate into a human body and thus disturb the harmonious function of systems

inside. The EM radiation propagating the human body will induce currents and

voltages which can interact with APs throughout the body. The interaction of the

interfering currents and voltages with APs over long period of exposure can create

havoc or confusion to the delicate electrical system of the body which is the nervous

system. This might be the starting of potential health hazards. It is extremely

important for research work to be undertaken to quantify the extent of the interaction

and how it could jeopardize the harmonious flow of the signals throughout the

human body.

1.3 Aim of research

The aim of the research is to investigate using circuit simulation and hardware

implementation that action potential in human arm can be disturbed by non-ionizing

electromagnetic radiation.

5

1.4 Objectives of research

The objectives of the research are as follows:-

(i) To model the electrical system of human arm as equivalent to combinations

of voltage sources, capacitors, inductors and resistors by using TL model

method

(ii) To analyse the effect of non-ionizing EM radiation on the AP in human arm

electrical model due to radiation distance, power, orientation and also due to

nerve fibre radius and its exposure area to the EM radiation

(iii) To verify the effect of non-ionizing EM radiation on the AP in human arm

electrical model by performing measurement to robotic arm signal with

appearance of GSM phones nearby

1.5 Scopes of research

Human arm nervous system which converted to electrical model in this research is a

human somatic nervous or peripheral nervous system. Connection of nerve fibres

from brain to arm is considered as equivalent circuit of lossless TL with the source of

the circuit is an action potential inside the nervous system of human body. The

source is modelled as the action potential by using Izhikevich simple spiking model

[15]. The electromagnetic radiation is produce by mobile phone with operating

frequency of 900 MHz. Purpose of using robotic arm to compare with human arm is

not by comparing in physical means, but to compare what will happen to the signal

inside the wires of robotic arm when there is radiation source placed near to the

robotic arm. It is just the same like situation in simulation circuit where the result is

observed on signal behaviour when radiation source appear.

1.6 Thesis organization

This study is presented in five chapters. The thesis begins with an introduction to

sources of EM radiation and how it could affect various human body systems. This

concern leads to study on electromagnetic radiation effects towards the AP in the

human nervous system. Chapter 2 is basically literature review about past study on

health hazards towards EM radiation, physiology of human nervous system and its

6

similarity with electrical circuit. Methodology on how this study is under taken is

discussed deeply in Chapter 3. This chapter include the modelling of nerve fibres

circuit and the setup of robotic arm experiment. Chapter 4 is focused on discussion of

results obtained from simulation process of nerve fibres circuit in term of its AP and

experimental results from the robotic arm movement and its signal correspond to

mobile phone radiation. Conclusions and future recommendations for this study were

briefly stated in Chapter 5.

7

CHAPTER 2

LITERATURE REVIEW

In this modernization era, people are exposed to EM radiation in their daily life due

to ever increasing usage of wireless communication device such as mobile phones

and base stations which are widely placed in human environment. As a consequence,

human body is continuously exposed to the EM radiation from those devices. Many

literatures came with conclusion that devices that emit microwaves are possible to

create health hazard towards animals and humans.

Deep understanding in physiology of human nervous system is very

important in producing an equivalent circuit of a neuron network. Literature on

previous neuron equivalent circuits has helped in producing new neuron network

equivalent circuit. Furthermore, many researchers that specialize in the field of brain

neural networks have produced different mathematical models that can be simulated

in mathematical software to produce AP that exist in neurons. All of other researches

worked will be discussed in this chapter soon.

Simple susceptibility model in electromagnetic compatibility field is a useful

model to quantify the interaction of EM radiation towards electrical system of human

body. Information from this model is crucial to be stated in the thesis to give better

understanding for readers about works done in this thesis. In addition, some

information about robotic arms and mobile phones that are used as experimental

hardware are listed as they are crucial in proving interaction of EM radiation towards

human body electrical system.

8

2.1 Relationship between EM radiation and health hazards

Mobile phones are one of the most commonly used and carried along by users.

Hence, mobile phones can become extremely effective source of EM radiation since

its usually on.

Bawin, Kaczmarek and Adey [16] and Foster [17] reported that since GSM

phone operates in a pulse mode and its signal is categorised as modulated EM

radiation, the signal may cause neurological effects even at low average power.

The Independent Expert Group on Mobile Phones (IEGMP) in the United

Kingdom has reported that children are more sensitive to EM radiation from mobile

phones compared to adults because of their smaller head and brain size, thinner

cranial bones and skin, thinner, more elastic ears, lower blood cell volume, as well as

greater conductivity of nerve cells [18].

Johansson [19] did an extensive literature review on the non-thermal effects

of EM radiation and concluded that there are a number of strong indications of EM

fields being capable of disturbing the immune system and thus increasing disease,

including cancer risk. He suggested that existing safety limits are inadequate to

protect public health and need to be reviewed to accommodate deployment of

untested technologies.

Guy and Chou [20] reported that a rat which exposed to a very high-intensity

microwave pulses has a temperature rise in its brain and seizures occurred to the rat

and followed by unconsciousness for 4 to 5 minutes. Postmortem revealed damage at

myelin sheaths of the rat nerve fibre.

Blackman [21] raises concerns about the possible health consequences on

non-thermal effects based on recent evidence from epidemiological studies

associating increases in brain and head cancers with increased cell phone use per day

and per year over 8-12 years. Furthermore, two of the studies did by Hardell, Mild

and Carlberg [22], have found that there are correlations between tumor's location

and side of the head where phone were held during a phone call.

Luria et al. [23] did a study on the cognitive functions of humans when

exposed to GSM radiation. 48 healthy right-handed males were given a specific task

and their response times were recorded. The study confirmed the existence of an

effect of the EM exposure on the hand response time and has correlation with

exposure time and location of the phones on the head.

9

Other studies [24, 25] revealed that non-thermal effects of EM exposure

show evidence of potential risk to health. Current EM exposure safety standards are

deemed inadequate to address this issue. Immediate adverse health effects are not

common but there are various other effects which can result in slow death or as silent

killers. The consequences might surface after years or perhaps in future generation.

2.2 Neurological electrophysiology effects of EM radiation

There are several studies mostly involving mobile phones at GSM 900 band as the

source of EM radiation towards the APs in nervous system. The behavioural and

physical changes happened to the APs due to the EM radiation is know as

neurological electrophysiology.

Bolashakov and Alekseev [26] found that non-continuous 900 MHz pulsed

wave radiation increased bursts of firing of Lymnea (freshwater snail) neurons. This

result correlates with finding from Hao et al. [27]. 47 rats exposed to 916 MHz, 10

W/m2 mobile phone EM radiation; 6 hours a day, 5 days a week for 10 weeks. The

neuron signals of one exposed rat and one control rat in the maze were obtained by

the implanted microelectrode arrays in their hippocampal regions. The hippocampal

neurons of exposed rat showed irregular firing patterns and more spikes with shorter

interspike interval during the whole experiment period. Furthermore, results from

rats searching for food in an eight-arm radial maze show the average completion time

and error rate of the exposure group were longer and larger than that of control

group. It indicates that the 916 MHz EM radiation influence learning and memory in

rats to some extent in a period during exposure.

Razavinasab, Moazzami and Shabani [28] did a study on electrophysiological

properties of CA1 pyramidal neurons which exposed to GSM radiation. 8 rats were

exposed to 900 MHz pulsed EM radiation for 6 hours per day. Whole cell recordings

in hippocampal pyramidal cells did show a decrease in neuronal excitability. Mobile

phone exposure was mostly associated with a decrease in the number of APs fired in

spontaneous activity. There was an increase in the amplitude of the

afterhyperpolarization (AHP) in AP of exposed rats compared with the control. The

results of the passive avoidance and Morris water maze assessment of learning and

memory performance showed that phone exposure significantly altered learning

acquisition and memory retention in exposed rats compared with the control rats.

10

Therefore, the study confirmed that exposure to mobile phones adversely affects the

cognitive performance of rats.

Meanwhile study by Partsvania et al. [29] show that after acute exposure of

900 MHz mobile phone radiation on single neurons of mollusk, average firing

threshold of the action potentials was not changed. However, the average latent

period was significantly decreased. This indicates that together with latent period the

threshold and the time of habituation might be altered during exposure. However,

these alterations are transient and only latent period remains on the changed level.

There are also study for different frequency of non-ionizing EM radiation on

action potential in a nerve. An early study from McRee et al. [30] has undergone an

experiment where the spinal cords of cats were directly exposed to 2450 MHz

continuous wave EM radiation in order to study the effect on reflex response and

synaptic function. APs recorded from the ventral root nerve were amplified 500 to

2000 times from its original signal with apperance of EM radiation. Meanwhile,

Seaman and Wachtel [31] observed a different result, which is increased in AP firing

rates of Aplysia (sea snail) ganglia that been exposed to 2.5 GHz continuous wave

EM radiation.

As several studies produce different behavioural and physical changes

towards the AP, the main concern here is the EM radiation do alter the AP.

Therefore, its essential to undertaken a study on EM radiation on AP in order to

quantify the extent of the interaction.

2.3 Physiology of human nervous system

Combination of neurons and brain create a system known as the nervous system.

Neurons are interconnected in a mesh of neural networks and convey information

among them or other target cells by using frequency modulated pulses known as AP

that course along an axon [32, 33]. Intracellular fluid inside of an axon or nerve fibre

is separated from extracellular fluid by a thin layer known as plasma membrane. It is

typically 4 nm to 10 nm in thickness and composed of a lipid bilayer embedded with

various types of protein molecules [34]. Voltage-gated sodium channel (voltage-

gated Na+ channel), voltage-gated potassium channel (voltage-gated K

+ channel),

sodium-potassium pump (Na+-K

+ pump) and leakage sodium channel (Na

+ leakage

channel) and leakage potassium channel (K+ leakage channel) are protein molecules

11

that have an active role in producing and retaining the AP inside the nerve fibre.

Production of AP involved several phases, starting from resting, depolarization,

repolarization, hyperpolarization and lastly return to resting [35].

At rest, nerve fibre intracellular fluid (ICF) voltage is -70 mV which also

known as resting potential. Some transport mechanism helped the axon to maintain

its ICF voltage which involves some protein molecules as mention in paragraph

above. The Na+-K

+ pump actively transports 3 Na

+ out of and 2 K

+ into the nerve

fibre, keeping the concentration of Na+ high in the extracellular fluid (ECF) and the

concentration of K+ high in ICF [30]. This uneven positive ions or cations transfer

resulting in higher concentration of cations in ECF compared to ICF. Furthermore,

the fact that the plasma membrane is permeable to K+ adding to factor of high

concentration of cations in ECF. Inexistence of any protein molecules that can

support transport mechanism for negative ions or anions in ICF and zero

permeability of anions towards the plasma membrane resulting in higher

concentration of anions compared to cations in ICF. Therefore, voltage difference

between ICF and ECF has produced the negative value of resting potential.

Actually, the plasma membrane is slightly permeable to Na+. This

characteristic has helped inward movement of Na+

into the nerve fibre. Inward of Na+

is very important to counterbalance outward movement of K+ from the nerve fibre

[36]. This two way processes have helped the nerve fibre to maintain its resting

potential always at -70 mV, instead of keep decreasing towards K+ equilibrium

potential because of its high permeability towards the membrane. Small portion of

Na+ that enters the nerve fibre will slowly increase the potential value in the nerve

fibre towards threshold potential. As a result, activation gates of some of its voltage-

gated Na+ channels to open. Na

+ starts to enter into the nerve fibre because of

concentration difference. The inward Na+ excites more voltage-gated Na

+ channels to

open its activation gates [36]. More Na+ is rushing into nerve fibre and produces

rapid increase of potential value inside the nerve fibre. The voltage increase process

is known as depolarization phase in AP.

During rapidity of voltage-gated Na+ channels opening its activation gate,

there is counterbalance process from inactivation gate ball that is slowly binding to

the channel opening. Therefore, there is interval of 0.5 ms between processes of

activation gates open and inactivation gates close [36]. This 0.5 ms interval has made

the nerve fibre depolarized until its AP reached the peak of +30 mV which is near to

12

Na+ equilibrium potential. Once the inactivation gate closed, the voltage-gated K

+

channels activation gate starts to slowly open at the peak of the AP [36]. K+ starts to

exit from the nerve fibre because of concentration difference. Consequently, the

potential value inside the nerve fibre is plummeting from its peak back to resting.

The voltage decrease process is known as repolarization phase in AP.

However, characteristics of voltage-gated K+ channels that are slow to close

have resulting in more K+ to leak from the nerve fibre. This process has made the

potential value inside the nerve fibre become more negative that the actual resting

potential. This process is known as hyperpolarization phase in AP. The

hyperpolarization does not last long since voltage-gated K+ channels activation gate

closing process will increase back the excess potential negative value during

hyperpolarization. Once the activation gates closes completely, the AP returns to it

resting phase. The whole phases create the AP as shown in Figure 2.1.

Understanding the creation of AP, has aided many researchers to produce

mathematical model of AP inside the brain which is essential as the source in

designing a neuron electrical circuit in this studies.

Figure 2.1: Action potential and its phases [35]

13

Correlation between central nervous system (CNS) and peripheral nervous

system (PNS) are very important to initiate motor control on muscle, so that the

muscle will moved according to human brain thought. Figure 2.2 illustrate the

organization of motor control for voluntary movement of a human arm. In voluntary

movement, an idea to move an arm is initiated in brain at primary motor cortex area.

The idea or information is carried by propagation of AP in a nerve fibre through

brain stem and spinal cord. Motor neuron that synapses in the spinal cord continues

the propagation of AP until reach muscle fibre to trigger an arm movement. The

movement event is sensed by a peripheral receptor that produces AP. The AP

propagates in an afferent neuron until reach the afferent neuron terminals at spinal

cord. The AP are now transmitted by other nerve fibre through brain stem and

cerebellum until the AP reaches the origin of primary motor cortex to continue the

arm movement. The propagation of AP in the motor control diagram is in a loop

which can be compared to a complete circuit model which will be discussed in next

chapter.

Figure 2.2: Motor control organization for muscle movement [36]

14

There are also movements by skeletal muscle which only involves efferent or

motor neurons. Those neurons form tracts from the brain to the skeletal muscle

which known as descending tracts as shown in Figure 2.3. The process of AP

propagation to realize a movement is same as explained in previous paragraph,

except there is no sensor to detect the movement event. Even though the AP

propagation are point to point movement, but the surrounding substance around the

neurons can be used as grounding in order to introduce a circuit model which also

will be discussed in next chapter.

Figure 2.3: Descending tracts for muscle motor neurons [36]

15

2.4 Neuron electrical circuits and action potential mathematical models

The history of neuro-computational science starts in 1950s when Hodgkin and

Huxley had formulated the nerve fibre AP in a squid giant axon. Earlier studies by

Hodgkin and Huxley [37, 38, 39] have show that, movement of Na+ and K

+ across

the plasma membrane can be represent as continuous time function conductance

because rapid conductivity of those ions across the membrane only happens at their

own specific time. The membrane that separate ICF and ECF can be consider as

capacitance. Adding with conductivity factor of those ions through the leakage

channels, the nerve fibre electrical network can be shown as in Figure 2.4.

RNa RK RL

VK VL

CM

VNa

extracellular fluid

intracellular fluid

Vm

INa IK IL

I

Figure 2.4: Hodgkin and Huxley nerve fibre electrical model [11]

Analysis for circuit in Figure 2.4 by using Kirchhoff’s Current Law produced

an equation of total membrane current during ion transportation process.

LKNa

m

M IIIdt

dVCI (2.1)

where I is the membrane total current density 2/ cmA

INa, IK, IL are the Na+, K

+, leakage ion current density 2/ cmA

Vm is the membrane potential mV

Cm is the membrane capacitance per unit area 2/ cmF

t is time ms

16

The individual ionic currents are presented by the relations:

NamNaNa VVgI (2.2)

KmKK VVgI (2.3)

Llmll VVgI (2.4)

where gNa, gK, lg are the Na

+, K

+, leakage ion conductance 2/ cmmS

VNa, VK, VL are the Na+, K

+, leakage ion equilibrium potentials mV

Hodgkin and Huxley use a theoretical power variables satisfying first order

kinetic equations curves to best fit Na+ and K

+ experimental conductance values

which are obtained from voltage clamp experiments on squid giant axonal membrane

[11, 32]. A part of this process has produced an assumption that K+ conductance is

proportional to K+ activation gating variable. Multiplying the variable by the

asymptotic value of K+ maximum conductance, a K

+ conductance formula is

introduced.

4ngg KK (2.5)

nndt

dnnn 1 (2.6)

where Kg is a constant 2/ cmmS

n is a K+ activation gating variable (unitless)

n ,

n are rate constants (ms -1

)

The first order kinetic equation defines the n gating variable which represents

the closing and opening of the activation gate K+ channels as shown in Figure 2.5.

The variable, n is vary between 0 and 1. The K+ conductance value is maximum

when n is equal to 1 while n equal to 0 indicates no K+ conductance value or no

voltage-gated K+ channels appear on the membrane.

17

Figure 2.5: Voltage-gated K+ channel in closed (on left) and opened (on right) states

[36]

The rate constants, n and

n are functions that dependent on membrane

potential, Vm but not with time even though its unit is inverse of time. As in K+

conductance experimental values, the experimental rate constants points are plotted

to their respective membrane voltage and continuous curves which are clearly a good

fit to the experimental data are applied. Hence, formulas of curves that represent both

rates constant are obtained.

1

5001.0501.0

mV

m

ne

V (2.7)

60125.0125.0

mV

n e (2.8)

Unlike K+ conductance, Na

+ conductance is proportional to two variables

instead of one. Those two variables are Na+ activation gate variable and Na

+

inactivation gate variable. Multiplying the variable by the asymptotic value of Na+

maximum conductance, a Na+ conductance formula is introduced.

hmgg NaNa

3 (2.9)

mmdt

dmmm 1 (2.10)

hhdt

dhhh 1 (2.11)

where Nag is a constant 2/ cmmS

m is a Na+ activation gating variable (unitless)

h is a Na+ inactivation gating variable (unitless)

m ,

m , h ,

h are rate constants (ms -1

)

18

The first order kinetic equation defines the m and h gating variables which

represent the closing and opening of both activation and inactivation gates of Na+

channels as shown in Figure 2.6. The variable, m and h are also varies between 0 and

1. Both gating variables have to be non-zero for the Na+ conduction to occur.

Figure 2.6: Voltage-gated Na+ channel in closed (on left), opened (at middle) and

inactive (on left) states [36]

Figure 2.6 showed that voltage-gated Na+ channels have three states rather

than two states for voltage-gated K+ channels. This is due to Na

+ conductance has

two separate gating variables, m and h. As seen in Figure 2.6, closed and opened

states are determined by the m gating variable that controls closing and opening of

activation gate during AP process. Inactive state is determined by the h gating

variable that controls the hanging ball which represents the inactivation gate in

Figure 2.6 during AP process.

Properties of rate constants, m ,

m , h and

h are the same as n and

n

of K+ conductance. The rate constants points from Hodgkin and Huxley [11]

experiments are plotted to their respective membrane voltage and continuous curves

which are clearly a good fit to the experimental data are applied. Hence, formulas of

curves that represent all of the rates constant are obtained.

1

351.0351.0

mV

m

me

V (2.12)

18/604

mV

m e (2.13) 6005.0

07.0

mV

h e (2.14)

1

1301.0

mVhe

(2.15)

One per unit circuit as shown in Figure 2.4 only can produce an AP when I=0

in Equation (2.1). Therefore, by solving Equation (2.1) until Equation (2.15) in a

19

simulation package such as PSPICE or MATLAB, an AP as in Figure 2.1 will be

obtained.

Analysis by Keynes et al. [40] towards their data in voltage clamp

experiments on barnacle muscle fibre, shows that two voltage dependent

conductance exist in muscle fibre membrane which are calcium (Ca2+

) conductance,

gCa and K+ conductance, gK. Both conductances are in function of membrane voltage.

Morris and Lecar [12] did a further studies based on Keynes findings in order to

produce a muscle fibre electrical as shown in Figure 2.7 which is quite similar with

Hodgkin and Huxley circuit except, the Ca2+

conductance is used instead of Na+

conductance.

RNa RK RL

VK VL

CM

VCa

extracellular fluid

intracellular fluid

Vm

ICa IK IL

I

Figure 2.7: Morris-Lecar electrical circuit model [12]

The equations describing the muscle fibre membrane behavior are obtained

from analysis of circuit in Figure 2.7 by using Kirchhoff’s Current Law.

LmLCamCaKmKm

M VVgVVMgVVNgdt

dVCI (2.16)

MMdt

dMM (2.17)

NNdt

dNN (2.18)

where I is the membrane total current density 2/ cmA


CM is the membrane capacitance per unit area 2/ cmF

t is time ms

20

gCa, gK, gL are the Ca2+

, K+, leakage ion conductance 2/ cmmS

VCa, VK, VL are the Ca2+

, K+, leakage ion equilibrium potentials mV

M, N are the Ca2+

, K+ opening gating variable (unitless)

M∞, N∞ are the Ca2+

, K+ steady state opening gating variable (unitless)

M , N are rate constants (ms

-1)

The variables M and N are analogous to the Hodgkin and Huxley [11] “m”

and “n” parameters [12]. M is gating variable that controls Ca2+

channels opening at

any given time while N is gating variable that controls K+ channels opening at any

given time.

Elementary statistical arguments in Lecar, Ehrenstein and Latorre [41] and

Ehrenstein and Lecar [42] have produced formulae for rate constants, M and N

and also steady state opening gating variable, M∞ and N∞.

21 /tanh15.0 VVVM m (2.19)

21 2/cosh VVVmMM (2.20)

43 /tanh15.0 VVVN m (2.21)

43 2/cosh VVVmNN (2.22)

where M , N are maximum rate constants (ms -1

)

V1, V3 are potential at which M∞ = N∞ = 0.5 (mV)

V2, V4 are M∞, N∞ reciprocal of slope of voltage dependence

Note: Values for the parameter in Equation (2.19) until equation (2.22) are

obtained from Morris and Lecar [12] voltage clamp experiment data.

21

At early stage of mathematical modelling by Hindmarsh and Rose [13] in

order to produce isolated bursting AP, they proposed two simultaneous first order

differential equations that can produce the bursting AP.

Ibxaxydt

dx 23 (2.23)

ydxcdt

dy 2 (2.24)

where x is the membrane potential (mV)

y is a recovery variable (unitless)

t is time ms

a, b, c, d are time constant (ms) [positive real number]

I is a stimulus current (nA)

Those equations are obtained through modification and transformation of

variables in earlier Hindmarsh and Rose model [43]. The drawback in model from

equations above is inexistent of hyperpolarization state on the produced AP.

Furthermore, an AP produced by the model has longer duration than actual AP. In

order to overcome the problems, they introduced another first order differential

equation that produces slow current. The slow current equation can give an ample

time for the AP to enter hyperpolarization state before reaches a resting state.

zIbxaxydt

dx 23 (2.25)

ydxcdt

dy 2 (2.26)

zxxsrdt

dz 1

(2.27)

where z is the membrane adaption current (nA)

x1 is the initial membrane potential (mV)

r, s are time constant (ms) [positive real number]

All the time constants have very important role in producing the required AP.

As a result, they have produce the isolated bursting AP that existing

hyperpolarization state as shown in Figure 2.8.

22

Figure 2.8: Isolated bursting AP produced by Hindmarsh and Rose model [13]

Subsequent investigations after Hodgkin and Huxley findings, have found

that the AP in nerve fibre of human are diverse in their spike patterns. Furthermore,

there are many ionic currents other than IK and INa that contributing to the AP

creation in the nerve fibre. Connors and Gutnick [44], Gutnick and Crill [45] and

Gray and McCormick [46] have categorized the diversity of neocortical neurons

spike patterns into four distinct classes which are regular spiking, fast spiking,

continuous bursting and intrinsic bursting neurons. Gutnick and Crill [45] and

McCormick [47] investigations have shown that approximately 12 ionic currents are

involved during AP propagation through the nerve fibre.

Analysis of the diversity of neurocortical ionic currents and AP spike patterns

has triggerd a development of simplest plausible mathematical model that is

consistent with dynamical behaviour of neocortical neurons [14]. The Wilson model

consist of four first order differential equations that are modified from original

Hodgkin and Huxley model with some reasonable approximation and with addition

of two more dominant ionic currents from others ionic current as mentioned in

Gutnick and Crill [45] and McCormick [47]. At early stage of Wilson model

development, the Hodgkin and Huxley model is modified and simplified until only

two first order differential equations are left.

23

IVVRgVVmdt

dVC KmKNam

m

m (2.28)

RRdt

dR

R

1 (2.29)

where I is a stimulus current (nA)


Cm is the membrane capacity per unit area (nF)

t is time ms

Kg is the K

+ maximum conductance S

VNa, VK are the Na+, K

+ equilibrium potentials mV

R is the K+

activation function (unitless)

m∞, R∞ are the Na+, K

+ steady state activation function (unitless)

R is a time constant (ms)

Voltage-gated Na+ channel activation time constant, τm is much smaller

compared to voltage-gated Na+ channel inactivation time constant, τh and also

voltage-gated K+ channel activation time constant, τn [11]. This means that the

activation of the Na+ channels is quite fast in reaching their steady state value.

Therefore Wilson takes this advantage by taking the activation m function is always

equal to steady state activation m∞ function by assuming the τn is too small until its

effects can be neglected. This approximation is supported by Rinzel [48] that

produced AP mathematical model by assuming Na+ channels activation are

sufficiently fast enough to be described by its steady state value m∞.

In order to reduce computation time in Wilson model, Na+ channels

inactivation gating variable, h is ignored. Again, according to Hodgkin and Huxley

[11] investigation, roughly same numerical value between τh and τn has triggered

Wilson to replace the effect of Na+ inactivation gating variable, h with the

comparable effect of K+ activation gating variable, n. Furthermore, observation of

human and mammalian neocortical neurons does not contain any inactivation Na+

currents [49, 50].

The final assumption by Wilson is the τr is chose to be independent of Vm or

in other words, τr is a real number rather than a function. This is possible because

Wilson used second order polynomial curve fit approximations that follow the

exponantial behaviour of activation gating variable n and m in Hodgkin and Huxley

24

model which are analogus to activation gating variable R∞ and m∞ in Wilson model

respectively.

Among other currents that responsible for creation of AP instead of IK and

INa, a low threshold Ca2+

current, IT and a slow afterhyperpolarizing (AHP) K+

current, IH are also dominant factor in AP propagation process. Therefore, by taking

into account IK, INa, IT and IH effects in AP creation and propagation, Wilson [14] has

proposed a mathematical model that consists of four first order differential equations

with each steady state activation functions are represent by second order polynomial

equations.

IVVHgVVTgVVRgVVmdt

dVC HmHTmTKmKNam

mm

(2.30)

RRdt

dR

R

1 (2.31)

TTdt

dT

T

1 (2.32)

THdt

dH

H

31

(2.33)

8.176.478.33 2 mm VVm (2.34)

24.17.32.3 2 mm VVR (2.35)

205.46.118 2 mm VVT (2.36)

where HT gg , are the Ca

2+, AHP K

+ dynamic conductance S

VT, VH are the Ca2+

, AHP K+ equilibrium potentials mV

T, H are the Ca

2+, AHP K

+ activation function (unitless)

T∞ is the Ca2+

steady state activation function (unitless)

T ,

H are time constants (ms)

Izhikevich [15] has produced a simple model of spiking neurons that is as

biologically plausible as the Hodgkin and Huxley model which it can produce

various firing patterns of neurons. Furthermore, it is computationally efficient with

very low number of floating point operation are needed in order to simulate it in

required duration if compared to real Hodgkin and Huxley model [51]. The first

version of this model was published in [52] but in trigonometric form in order to ease

the mathematical analysis. Then, Izhikevich transform the model so it can perform

large-scale simulations.

120

REFERENCES

[1] K.-H. Ng, "Non-ionizing radiations – sources, biological effects, emissions and

exposures," in Proceedings of the International Conference on Non-Ionizing

Radiation (ICNIR2003), UNITEN, October 2003.

[2] T. Björn, M. L. Strydom, B. Hansson, F. J. C. Meyer, K. Karkkainen, P.

Zollman, S. Ilvonen and C. Tornevik, "On the estimation of SAR and

compliance distance related to RF exposure from mobile communication base

station antennas," IEEE Transaction on Elctromagnetic Compatibility, vol. 50,

no. 4, pp. 837-848, 2008.

[3] "Report from the commission on the application of council recommendation of

12 July 1999 (1999/519/Ec) on the limitation of the exposure of the general

public to electromagnetic fields (0 Hz to 300 GHz)," Comission of the European

Communities, Brussels, 2008.

[4] M. A. A. Karunarathna and I. J. Dayawansa, "Energy absorption by the human

body from RF and microwave emissions in Sri Lanka," Sri Lankan Journal of

Physics, vol. 7, pp. 35-47, 2006.

[5] A. Davidson, "Electromagnetic fields from non-ionising electromagnetic

radiation : h.e.s.e. project," Human Ecological Social Economical-UK, 2013.

[Online]. Available: http://www.hese-project.org/hese-uk/en/niemr/index.php.

[Accessed 24 June 2013].

[6] ICNIRP, "Guidelines for limiting exposure to time-varying electric, magnetic,

and electromagnetic fields (up to 300 GHz)," International Commision on Non-

Ionizing Radiation Protection Publication , vol. 74, no. 4, pp. 494-522, 1998.

[7] "Basic standard for the calculation and measurement of electromagnetic field

strength and SAR related to human exposure from radio base stations and fixed

terminal stations for wireless telecommunication systems (110MHz to 40GHz),"

CENELEC EN50383, BTech.Committee 211, European Committee for

Electrotechnique Standardization (CENELEC), August 2002.

[8] "Determination of RF fields in the vicinity of mobile communication base

stations for the purpose of evaluating human exposure," IEC62232 Ed.1CD,

2008.

[9] K. Patton and G. Tibodeau, Anatomy & Physiology, 7th ed., Elsevier, 2010.

[10] L. Standley, "Peripheral Nervous System: Dr Standley," 2000. [Online].

Available: http://www.drstandley.com/bodysystems_peripheralnervous.shtml.

[Accessed 24 June 2013].

[11] A. L. Hodgkin and A. F. Huxley, "A quantiative decription of membrane current

and application to conduction and excitation in nerve," Journal of Physiology,

vol. 117, no. 4, pp. 500-544, 1952.

121

[12] C. Morris and H. Lecar, "Volatage oscillations in the barnacle giant muscle

fibre," Jounal of Biophysiology, vol. 35, no. 1, pp. 193-213, 1981.

[13] J. L. Hindmarsh and R. M. Rose, "A Model of neuronal bursting using three

coupled first order differential equations," Proceedings of the Royal Society of

London, vol. 221, no. 1222, pp. 87-102, 1984.

[14] H. R. Wilson, "Simplified dynamics of human and mammalian neocortical

neurons," Journal of Theoritical Biology, vol. 200, no. 4, pp. 375-388, 1999.

[15] E. M. Izhikevich, "Simple model of spiking neurons," IEEE Transaction of

Neural Networks, vol. 14, no. 6, pp. 1569-1572, November 2003.

[16] S. M. Bawin, L. K. Kaczmarek and W. R. Adey, "Effect of modulated VHF

fields on the central nervous system," Annals of the New York Academy of

Sciences, vol. 247, no. 1, pp. 74-80, 1975.

[17] K. R. Foster, "Interaction of radiofrequency fields with biological system as

related to modulation," in International Seminar on Biological Effects of Non-

Thermal Pulsed and AM, RF, EMF and Related Health Risks, Munich Germany,

November 1996.

[18] "Mobile phones and health," Independent Expert Group on Mobile Phones

(IEGMP), United Kingdom, May 2000.

[19] O. Johansson, "Disturbance of the immune system by electromagnetic fields—A

potentially underlying cause for cellular damage and tissue repair reduction

which could lead to disease and impairment," Pathophysiology, vol. 16, no. 2,

pp. 157-177, 2009.

[20] A. W. Guy and C. K. Chou, "Effects of high-intensity microwave pulse

exposure of rat brain," Radio Science, vol. 17, no. 5, pp. 169-178, 1982.

[21] C. Blackman, "Cell phone radiation: Evidence from ELF and RF studies

supporting more inclusive risk identification and assessment," Pathophysiology,

vol. 16, no. 2, pp. 205-216, 2009.

[22] L. Hardell, K. H. Mild and M. Carlberg, "Further aspects on cellular and

cordless telephones and brain tumors," International Journal of Oncology, vol.

22, no. 2, pp. 399-407, 2003.

[23] R. Luria, I. Eliyahu, R. Hareuveny, M. Margaliot and N. Meiran, "Cognitive

effects of radiation emitted by cellular phones: The influence of exposure side

and time," Bioelectromagnetics, vol. 30, no. 3, pp. 198-204, 2009.

[24] G. Abdel-Rassoul, O. Abou El-Fateh, M. Abou Salem, A. Michael, F. Farahat,

M. El-Batanouny and E. Salem, "Neurobehavioral effects among inhabitants

around mobile phone base stations," Neurotoxicology, vol. 28, no. 2, pp. 434-

440, 2007.

122

[25] A. Agarwal, F. Deepinder, R. K. Sharma, G. Ranga and J. Li, "Effect of cell

phone usage on semen analysis in men attending infertility clinic: An

observational study," Fertility and Sterility, vol. 89, no. 1, pp. 124-128, 2008.

[26] M. Bolshakov and S. Alekseev, "Bursting responses of Lymnea neurons to

microwave radiation," Bioelectromagnetics, vol. 13, no. 2, pp. 119-129, 1992.

[27] D. Hao, L. Yang, S. Chen, J. Tong, Y. Tian, B. Su, S. Wu and Y. Zeng, "Effects

of long term electromagnetic field exposure on spatial learning and memory in

rats," Neurological Sciences, vol. 34, no. 2, pp. 157-164, 2013.

[28] M. Razavinasab, K. Moazzami and M. Shabani, "Maternal mobile phone

exposure alters intrinsic electrophysiological properties of CA1 pyramidal

neurons in rat offspring," Toxicology and Industrial Health, 2014.

[29] B. Partsvania, T. Sulaberidze, L. Shoshiasvili and Z. Modebadze, "Acute effect

of exposure of mollusk single neuron to 900-MHz mobile phone radiation,"

Electromagnetic Biology and Medicine, vol. 30, no. 3, pp. 170-179, 2011.

[30] D. I. McRee, J. A. Elder, M. I. Gage, L. W. Reiter, L. S. Rosenstein, M. L.

Shore, W. D. Galloway, W. R. Adey and A. W. Guy, "Effects of nonionizing

radiation on the central nervous system, behavior, and blood: A progress

report," Environmental Health Perspectives, vol. 30, pp. 123-131, 1979.

[31] R. L. Seaman and H. Wachtel, "Slow and rapid responses to CW and pulsed

microwave radiation by individual Aplysia pacemakers," The Journal of

Microwave Power, vol. 13, no. 1, pp. 77-86, 1978.

[32] T. F. Weiss, Cellular Biophysics Electrical Properties, vol. 2, Massachusetts:

MIT Press, 1996.

[33] J. T. Hansen, Netter's Anatomy Coloring Book, 1st ed., Philadelphia: Saunders

Elsevier, 2010.

[34] R. Hine, Membrane: The Facts on File Dictionary of Biology, 3rd ed., New

York: Checkmark, 1999.

[35] B. Kolb and I. Q. Whishaw, Fundamentals of Human Neuropsychology, 6th ed.,

New York: Worth Publishers, 2009.

[36] L. Sherwood, Human Physiology, 7th ed., Belmont: Brooks/Cole Cengage

Learning, 2010.

[37] A. L. Hodgkin and A. F. Huxley, "Currents carried by sodium and potassium

ions through the membrane of the giant axon of Loligo," Journal of Physiology,

vol. 116, no. 4, pp. 449-472, 1952.

[38] A. L. Hodgkin and A. F. Huxley, "The components of membrane conductance

in the giant axon of Loligo," Journal of Physiology, vol. 116, no. 4, pp. 473-496,

1952.

123

[39] A. L. Hodgkin and A. F. Huxley, "The dual effect of membrane potential on

sodium conductance in the giant axon of Loligo," Journal of Physiology, vol.

116, no. 4, pp. 497-506, 1952.

[40] R. D. Keynes, E. Rojas, R. E. Taylor and J. Vergara, "calcium and potassium

systems of a giant barnacle muscle fibre under membrane potential control," The

Journal of Physiology, vol. 229, no. 2, pp. 409-455, 1973.

[41] H. Lecar, G. Ehrenstein and R. Latorre, "Mechanism for channel gating in

excitable bilayers," Annals of the New York Academy of Science, vol. 264, no. 1,

pp. 304-313, 1975.

[42] G. Ehrenstein and H. Lecar, "Electrically gated ionic channels in lipid bilayers,"

Quarterly Reviews of Biophysics, vol. 10, no. 1, pp. 353-383, 1977.

[43] J. L. Hindmarsh and R. M. Rose, "A model of the nerve impulse using two first

order differential equations," Letters to Nature, vol. 296, pp. 162-164, 1982.

[44] B. W. Connors and M. J. Gutnick, "Intrinsic firing patterns of diverse

neocortical neurons," Trends in Neurosciences, vol. 13, no. 3, pp. 99-104, 1990.

[45] M. J. Gutnick and W. E. Crill, "The cortical neuron as an electrophysiological

unit," in The Cortical Neuron, New York, Oxford University Press, 1995, pp.

33-51.

[46] C. M. Gray and D. A. McCormick, "Chattering cells: superficial pyramidal

neurons contributing to the generation of synchronous oscillations in the visual

cortex," Science Journals, vol. 274, no. 5284, pp. 109-113, 1996.

[47] D. A. McCormick, "Membrane properties and neurotransmitter actions," in The

Synaptic Organization of the Brain, New York, Oxford University Press, 1998,

pp. 37-75.

[48] J. Rinzel, "Excitation dynamics: insights from simplified membrane models,"

Federation Proceedings, vol. 44, no. 15, pp. 2944-2946, 1985.

[49] B. W. Connors and M. J. Gutnick, "Electrophysiological properties of

neocortical neurons in vitro," Journal of Neurophysiology, vol. 48, no. 6, pp.

1302-1320, 1982.

[50] M. Avoli, G. G. C. Hwa, J.-C. Lacaille, A. Olivier and J.-G. Villemure,

"Electrophysiological and repetitive firing properties of neurons in the

superficial/middle layers of the human neocortex maintained in vitro,"

Experimental Brain Research, vol. 98, no. 1, pp. 135-144, 1994.

[51] E. M. Izhikevich, "Which model to use for cortical spiking neurons?," IEEE

Transactions on Neural Networks, vol. 15, no. 5, pp. 1063-1070, 2004.

[52] E. M. Izhikevich, "Neural excitability, spiking and bursting," International

Journal of Bifurcation and Chaos, vol. 10, no. 6, pp. 1171-1266, 2000.

124

[53] E. M. Izhikevich, Dynamical Systems in Neuroscience: The Geometry of

Excitability and Bursting, London: MIT Press, 2007.

[54] C. Paul, Introduction to Electromagnetic Compatibility, 2nd ed., New Jersy:

Wiley-Interscience, 2006.

[55] OWI, "Robotikits Direct," OWI Incorporated, [Online]. Available:

http://www.owirobot.com/robotic-arm-edge-1. [Accessed 22 August 2013].

[56] L. Angrave, "OWIRoboticArm," University of Illinois, 29 August 2010.

[Online]. Available:

https://wiki.engr.illinois.edu/display/cs125wiki/OWIRoboticArm. [Accessed 22

August 2013].

[57] M. A. Jensen and Y. Rahmat-Samii, "EM interaction of handset antennas an a

human in personal communications," Proceedings of the IEEE, vol. 83, no. 1,

pp. 7-17, 1995.

[58] L. Le-Wei, K. Pang-Shyan, L. Mook-Seng, C. Hse-Ming and Y. Tat-Soon,

"FDTD Analysis of electromagnetic interactions between handset antennas and

the human head," in Asia Pacific Microwave Conference, Hong Kong, 1997.

[59] A. B. Lavanya, "Effects of electromagnetic radiation on biological systems: a

short review of case studies," in 8th International Conference on

Electromagnetic Interference and Compatibility, Chennai, 2003.

[60] R. Moe, "Overview of the GSM system and protocol architecture," IEEE

Communications Magazine, vol. 31, no. 4, pp. 92-100, 1993.

[61] TI, "Texas Instrument," [Online]. Available:

http://www.ti.com/ww/cn/uprogram/share/ppt/c5000/21modulation_v110.ppt.

[Accessed 26 August 2013].

[62] P. Vecchia, R. Matthes, G. Ziegelberger, J. Lin, R. Saunders and A. Swerdlow,

"Exposure to high frequency electromagnetic fields, biological effects and

health consequences (100 kHz-300 GHz)," International Commission on Non-

Ioninzing Radiation Protection (ICNIRP), Oberschleißheim, 2009.

[63] J. L. Hindmarsh and R. M. Rose, "A model of neuronal bursting using three

coupled first order differential equations," Proceedings of the Royal Society of

London, vol. 221, no. 1222, pp. 87-102, 1984.

[64] D. Andereuccetti, R. Fossi and C. Petrucci, "Dielectric Properties of Body

Tissues in the Frequency Range 10 Hz to 100 GHz," "Nello Carrara" Institute of

Applied Physics, 1 January 1997. [Online]. Available:

http://niremf.ifac.cnr.it/tissprop/. [Accessed 27 August 2013].

[65] CST, "CST Microwave Studio: Reference Value and Normalizing," CST,

Darmstadt, 2011.

125

[66] S. K. Yee and M. Z. M. Jenu, "Shielding effectiveness of concrete with graphite

fine powder in between 50MHz to 400MHz," in 2013 Asia-Pacific International

Symposium and Exhibition on Electromagnetic Compatibility, Melbourne, 2013.

[67] J. B. Hursh, "Conduction velocity and diameter of nerve fibers," American

Journal of Physiology, vol. 127, pp. 131-139, 1939.

[68] F. T. Ulaby, "Transmission Lines," in Fundamentals of Applied

Electromagnetics , New Jersy, Pearson Education Inc, 2007, p. 41.

[69] S. Deutsch and A. Deutsch, Understanding the Nervous System: An

Engineering Perspective, IEEE Press, 1993.

[70] A. L. Hodgkin, "The conduction of the nerve impulse," Liverpool University

Press, vol. 1065, 1964.

[71] M. Bove, G. Massobrio, S. Martinoia and M. Grattarola, "Realistic simulations

of neurons by means of an ad hoc modified version of SPICE," Biological

cybernetics, vol. 71, no. 2, pp. 137-145, 1994.

[72] W. Peasgood, L. A. Dissado, C. K. Lam, A. Armstrong and W. Wood, "A novel

electrical model of nerve and muscle using Pspice," Journal of Physics D:

Applied Physics, vol. 36, no. 4, pp. 311-329, 2003.

[73] T. Iijima, Action Anatomy: For Gamers, Animators, and Digital Artists, Japan:

Harper Design, 2005.

[74] B. G. Gragg and P. K. Thomas, "The relationships between conduction velocity

and the diameter and internodal length of peripheral nerve fibres," The Journal

of Physiology, vol. 136, no. 3, pp. 606-614, 1957.

[75] ETSI, "Digital cellular telecommunications system (phase 2+); Radio

transmission and reception (3GPP TS 05.05 version 8.20.0)," ETSI, Sophia

Antipolis, France, 1999.

[76] E. Calabro and S. Magazu, "Measurement of output power density from mobile

phone as a function of input sound frequency," Journal of Microwave Power

and Electromagnetic Energy, vol. 47, no. 4, pp. 270-279, 2013.

[77] M. Kahabka, "Pocket Guide for Fundamentals and GSM Testing," Wandel &

Goltermann GmbH, Eniugen u.A., 2013.

[78] "Wikipedia," Wikipedia Foundation, 15 January 2001. [Online]. Available:

http://de.wikipedia.org/wiki/Datei:Felder_um_Dipol.jpg. [Accessed 8 January

2014].

[79] L. J. Chamberlain, Long Term Functional and Morphological Evaluation of

Peripheral Nerve Regenerted Through Degradeable Collagen Implants,

Massachusetts: MIT M.S. Thesis, 1994.

126

[80] "Learn EMC," 2011. [Online]. Available:

http://www.learnemc.com/tutorials/Shielding01/Shielding_Theory.html.

[Accessed 1 October 2014].

[81] K. Susuki, "Myelin: A specialized membrane for cell communication," Nature

Education, vol. 9, no. 59, 2010.

non-ionizing electromagnetic radiation effects on...

Documents