design and implementation of an impedance analyzer based on
TRANSCRIPT
DEGREE PROJECT, IN , SECOND LEVELMEDICAL ENGINEERING
STOCKHOLM, SWEDEN 2015
Design and implementation of animpedance analyzer based onArduino Uno
A PILOT STUDY OF BIOELECTRICALIMPEDANCE ANALYSIS
JING WANG
KTH ROYAL INSTITUTE OF TECHNOLOGY
SCHOOL OF TECHNOLOGY AND HEALTH
I
Examensarbete inom medicinsk
teknik (HL202X) 30hp 2014:13
Design and implementation of an impedance analyzer based on Arduino Uno
Technology and Health Jing Wang
Godkänt
2015-03-25
Recensent Kaj Lindecrantz
Handledare
Farhad Abtahi
Uppdragsgivare
Mats Nilsson
Sammanfattning Mätning med elektrisk bioimpedans är vida använt idag för medicinsk övervakning.
Användningsområden inkluderar bland annat bedömning av kroppssammansättning,
uppskattning av nutritionsstatus och detektering av cancer. Modaliteterna för att tolka
informationen från elektrisk bioimpedans har också utvecklats snabbt över de senaste årtionden,
från analys med en frekvens till spektrum och bilder.
Biompedans erhålls genom att ta fram sambandet mellan ström och spänning. I ett strömbaserat
bioimpedans‐system har spänningsskällans stabilitet en stor inverkan på systemets
prestanda. Det här examensarbetet jämförde tre olika spänningsstyrda strömkällor: en
förbättrad Howland‐krets, en load‐in‐the‐loop‐krets drivs av en ström transportör och en krets
med dubbeloperativförstärkare. Dessa kretsar simulerades i Multisim och producerades sedan
som prototyper och testades i labb.
Försök har även gjorts med att generera och samla in signaler med digital‐analog omvandling
och analog‐digital omvandling. De kontrollerades av Arduino Uno och impedans analyserades
i Matlab.
III
Master of Science Thesis in Medical Engineering (HL202X) 30 credits
2014:13
Design and implementation of an impedance analyzer based on Arduino Uno
Technology and Health Jing Wang
Approved
2015-03-25
Reviewer
Kaj Lindecrantz
Supervisor
Farhad Abtahi Examiner
Mats Nilsson
Abstract Electrical bioimpedance measurement is widely used today for monitoring body condition. The
applications include and go beyond, body composition assessment, nutritional status
evaluation, and cancer detection. The modalities for interpreting the impedance information
have also developed quickly over the recent decades from single frequency bioimpedance
analysis to spectrum and to images.
Bioimpedance is measured by computing the relationship between voltage and current. In a
current based bioimpedance measurement system, the stability of current source has a large
influence on the performance of the system. This thesis compared three different voltage
controlled current sources: enhanced Howland circuit, load‐in‐the‐loop circuit driven by a
current conveyor and double operational amplifiers circuit. These circuits were simulated in
Multisim and manufactured into prototypes and tested in lab.
Effort has also been made to generate and collect signals with digital‐to‐analog convertor and
analog‐to‐digital convertor. They were controlled by Arduino Uno and impedance was
analyzed in Matlab.
IV
ACKNOWLEDGEMENT
First I would like to thank my supervisor Farhad Abtahi for his invaluable support and
guidance during the project.
I would also like to thank all my friends here for their company.
Finally, I would like to thank my parents who have supported me and have been waiting for
me throughout the whole master program.
Jing Wang
Stockholm, January, 2015
NOMENCLATURE
Notations
Symbol Description
Z Impedance (Ohm)
R Resistance (Ohm)
X Reactance (Ohm)
I Current (A)
V Voltage (V)
ω Frequency (rad/s)
Y Admittance (S)
G Conductance (S)
B Susceptance (S)
C Capacitance (F)
σ Conductivity (S/cm)
ε Permittivity (F/cm)
Re Resistance of extracellular fluid (Ohm)
Ri Resistance of intracellular fluid (Ohm)
Rm Resistance of membrane (Ohm)
Cm Capacitance of membrane (F)
Abbreviations
EBI Electrical bioimpedance
BCA Body composition assessment
BIS Bioelectrical impedance spectroscopy
ADC Analog to digital convertor
DAC Digital to analog convertor
VCCS Voltage controlled current source
ECF Extracellular fluid
ICF Intracellular fluid
SNR Signal‐to‐noise ratio
QD Quadrature demodulation
CMRR Common mode rejection ratio
VIII
Op‐Amp Operational amplifier
DOA Double operational amplifier
I2C Inter‐integrated circuit
SPI Serial peripheral interface
IDE Integrated development environment
DDS Direct digital synthesis
GUI Graphical user interface
TABLE OF CONTENTS
ACKNOWLEDGEMENT _________________________________________________________________ V
NOMENCLATURE ____________________________________________________________________ VII
TABLE OF CONTENTS _________________________________________________________________ IX
1 INTRODUCTION _____________________________________________________________________ 1
1.1 Background ____________________________________________________________________ 1
1.2 Purpose _______________________________________________________________________ 1
1.3 Outline ________________________________________________________________________ 1
2 THEORETICAL FRAMEWORKS __________________________________________________________ 3
2.1 Circuit theory ___________________________________________________________________ 3
2.2 Electrical properties of living tissue _________________________________________________ 4
2.3 Bioimpedance measurement system design __________________________________________ 6
2.4 Communication protocol __________________________________________________________ 9
2.4 Arduino Uno ___________________________________________________________________ 10
3 METHODS ______________________________________________________________________ 13
3.1 System Implementation __________________________________________________________ 13
3.2 Source generation ______________________________________________________________ 13
3.3 VCCS _________________________________________________________________________ 15
3.4 Signal measurement ____________________________________________________________ 18
3.5 Results display _________________________________________________________________ 21
4 RESULTS __________________________________________________________________________ 23
4.1 Signal generation _______________________________________________________________ 23
4.2 VCCS _________________________________________________________________________ 23
4.3 Signal measurement and display __________________________________________________ 27
5 DISCUSSION ______________________________________________________________________ 29
5.1 Impedance measurement system _________________________________________________ 29
5.2 Safety considerations ___________________________________________________________ 30
6 CONCLUSIONS _____________________________________________________________________ 31
7 FUTURE WORK ____________________________________________________________________ 32
8 EXPERIENCE GAINED _______________________________________________________________ 33
REFERENCES _____________________________________________________________________ 35
10
1 INTRODUCTION
1.1 Background
Electrical bioimpedance (EBI) technology measures electrical properties of biological materials
by means of applying electrical current/voltage to the whole material or regions of interest,
sensing corresponding voltage/current and calculating the impedance by using Ohm’s law. EBI
value is related to both the resistive and dielectric properties and the geometrical dimensions of
the material, so it is possible to monitor not only material composition but also volume. Over
the years, research interest on EBI has raised to develop new methods for patient monitoring
and diagnosis. Bioimpedance research applications include but are not limited to body
composition assessment (BCA) (1), skin cancer detection (2), impedance cardiography (3), breast
cancer detection (4), and cerebral monitoring (5). However, in many cases, due to inaccurate
models, presence of artefacts, errors in measurement and estimation of bioimpedance, they
have not been widely accepted in clinical applications (6).
Bioimpedance instrumentation by using system‐on‐chips (e.g. AD5933) can provide an
affordable framework for developing compact systems (7). However, their applications are
currently limited to single‐frequency measurements or bioelectrical impedance spectroscopy
(BIS) by using frequency‐sweep technique that estimates bioimpedance in one single frequency
at a time and repeat to measure a spectrum. To study different source of errors in bioimpedance
measurements and estimation, access to current/voltage signals prior to impedance estimation
is desired which requires custom design of measuring device. This device can be also useful in
study of BIS by using broadband excitation of waveforms like square wave, step function, chirp
and multi‐sine.
1.2 Purpose
The object of this thesis project is to design a bioimpedance measuring device with an analog to
digital convertor (ADC), a digital to analog convertor (DAC), a voltage controlled current
source (VCCS) and an Arduino board working as a microcontroller. By building the whole
system from scratch, the aim was to understand the system from each component, test the
possibility of building it with lower cost and make suggestions for further improvement.
To achieve this goal, this project is divided into following tasks:
to simulate and compare different VCCS configurations;
to make prototypes for the VCCSs and test in lab;
to create a voltage source with DAC and Arduino Uno;
to collect electrical signal with ADC and Arduino Uno;
to collect samples from Arduino Uno in Matlab;
to calculate and display the impedance in Matlab;
1.3 Outline
This thesis is divided into eight chapters. Chapter Two contains the background knowledge
about bioelectrical impedance, earlier research on BIS system design, BIA applications and
knowledge about communication protocol and the microcontroller Arduino Uno. Chapter
2
Three describes the methods and components used in the project. Chapter Four presents results
of the simulation and lab test of VCCS and presentation of signal generation and collection.
Results are discussed in Chapter Five. Chapter Six is the conclusion of the whole project.
Chapter Seven describes the future work to improve the project and suggest alternatives to the
component or the method used. And the last chapter is about the experience gained from the
project.
2 THEORETICAL FRAMEWORKS
2.1 Circuit theory
2.1.1 Electrical impedance
Electrical impedance (Z) is a measure of opposition to the current flow in a circuit (Figure 1). It
can be written as a complex in the Cartesian form or the polar form:
jZ R j X Z e . [1]
The real part R is the resistance, the imagery part X is the reactance,| | is the magnitude of
impedance and is the phase difference between the applied voltage (V) and corresponding
current (I). Resistance causes energy loss in the circuit. It won’t lead to any phase shift between
current and voltage. Reactance stores energy and causes phase difference between voltage and
current. Usually reactance is introduced by capacitors or inductors in the circuit. (8)
Electrical impedance can be calculated from Ohm’s law:
VZ
I . [2]
Figure 1 The impedance vector.
Figure 2 An example of phase delay.
2.1.2 Dielectric properties of materials
The electrical properties of materials can also be expressed as admittance Y, which is the inverse
of impedance. The formula, with capacitive components in the circuit, can be written as:
0
1rY G jB G j C K j K j
Z [3]
The real part G is called conductance. The imaginary part B is the susceptance. A capacitor is
drawn in Figure 3. Assuming the area of electrodes is A and the distance between two planes is
d, then K is the ratio between area and distance: K = A/d. is the conductivity of the material. It
4
is a measure of the material’s ability to conduct a current. And is the permittivity of the
medium between two planes which can be further extended to , where is the relative
permittivity of the material and is the dielectric permittivity of vacuum. This parameter is
related to the polarization of medium in response to the electric field. A high permittivity
denotes easy transmittance of electric field through the medium. is the frequency of the
applied electric field. (8)
Figure 3 A capacitor model.
2.2 Electrical properties of living tissue
2.2.1 Cell model
A cell is the most fundamental structural and functional unit in living tissues. The cell
membrane, which has a phospholipid bilayer structure, separates the intracellular fluid (ICF)
from the extracellular fluid (ECF). The intracellular and extracellular mediums are both
electrolytes. They contain ions that can move around the fluid, transport electrical charges and
therefore conduct electrical currents. The concentrations of some major ions in ICF and ECF are
shown in Table 1.
Table 1 Concentration of major ions in body liquids. Adapted from (9)
Concentration
(meq/L)
Na+ K+ Ca2+ Mg2+ Cl‐ HCO3‐ Protein HPO42‐
ICF 10 100 ‐ 123 2 8 55 149
ECF 142 5 5 2 105 24 16 2
The cell membrane can be considered as a dielectric. It has a very low conductance. So the ECF,
membrane and ICF form a conductor‐dielectric‐conductor structure, which is an analogy to a
capacitor in the circuit.
To study electrical properties of living tissues, it is of great help to establish an equivalent
electrical circuit for the cells. According to the characteristics introduced above, the ECF can be
depicted as a single resistor (Re). The ICF contains not only electrolytes but also organelles that
could introduce dielectric properties. For simplification, it is also modeled as a resistor (Ri). The
cell membrane is equivalent to a resistor connected in parallel with a capacitor (Rm||Cm). (8)
See Figure 4.
Figure 4 Equivalent electrical model of a cell. Re represents resistance of ECF. Ri represents resistance of
ICF. Rm represents resistance of membrane. And Cm represents capacitance of membrane. (8)
Based on the model introduced above, the impedance of a cell can be written as:
11
1e i
e ie i
R j CRZ R R
j C j C R R
[4]
At low frequencies, the electrical current is impeded by the membrane. So the ECF plays a
major role in conducting electrical current. In the extreme case, when a DC current is applied,
the measured signal would be related only to ECF. This could also be demonstrated with the
equation above. When the frequency → 0, the expression for the impedance could be written
as:
eZ R . [5]
At high frequencies, the electrical current passes through the membrane and the measurement
is dependent on both ECF and ICF.
2.2.2 β dispersion
The dielectric properties of living tissues and cell suspensions have a dispersive behavior in
response to electrical currents. This means their dielectric properties like permittivity and
conductivity depends on frequency. According to the changes in permittivity and conductivity,
Schwan defined three major dispersions: α, β and γ dispersion. A fourth dispersion widow, δ dispersion, between β and γ dispersion has also been noticed. (10)
6
Figure 5 Frequency dependence of permittivity and conductivity of living tissue (11).
β dispersion includes the frequency range from 1kHz to several Mhz. This dispersion is
considered to be related to the behavior of membrane. The properties of cells are mainly
influenced by dielectric properties of membrane and the process of charging and discharging
the membrane. Because of this reason, the measurement of electrical bioimpedance is usually
performed in this range. And for single frequency bioimpedance analysis, the frequency is
typically 50kHz.
2.3 Bioimpedance measurement system design
There are two methods to obtain the impedance. One is to inject an electrical current and
measure the corresponding voltage. Another method is to apply voltage to the object of interest
and measure the current. Both methods are used in bioimpedance measurement, and both have
their advantages and limitations. Compared to the BIA device that applies voltage to the target,
the current based BIA is able to manage currents within medical safety limits more easily.
Besides, it suffers less noise due to spatial variation and produces better bioimpedance
tomography results. However, current source gives poor performance at high frequency due to
its decreased output impedance. Voltage sources applications work with higher bandwidth,
however low dc SNR. (12) The current source based BIA is more commonly used in the EBI
measurement devices today. In this thesis work, the focus will be the impedance measurement
system with a current source.
2.3.1 Electrodes and connection
Bioimpedance measurement devices typically consist of two major functions: first inject an
alternating current to the biological material and then measure the potential difference from
two ends. Fulfilling these two functions requires two, three or four electrodes (13). Two‐
electrode method and four‐electrode are introduced here. Three‐electrode method is not very
common. One example using three‐electrode method can be found in (14).
Two‐electrode method
The two‐electrode method or bipolar method uses two electrodes to inject a known current to
the biological material and measures the voltage drop over this material from the same
electrodes. See Figure 6. Apart from the impedance of biological material Zm, the impedances at
two electrode contacts Zc are also included in the measured impedance.
Figure 6 Biopolar bioimpedance measurement system (a) and its equivalent electrical circuit (b).
So the two‐electrode method only works when the impedance of the tested material is much
higher than the impedance of electrode contacts at the BIA working frequency. If a BIS device is
used, two‐electrode method is not an option because the impedance at electrode‐electrolyte
interface is susceptible to frequency variations. (15)
Four‐electrode system
The four‐electrode system is also known as tetrapolar system. It uses separate electrode pairs to
inject current and measure voltage.
Figure 7 Tetrapolar bioimpedance measurement system (a) and its equivalent electrical circuit (b).
Assuming the voltmeter is ideal, the measurement result will involve only the impedance of the
tested material. This makes the four‐electrode method most commonly used in today’s
bioimpedance measurement.
In practice, however, the impedance at the contact sites still has an impact on the measurement
because of common voltage introduced by contacts’ impedance and common mode rejection
ratio (CMRR) of the differential amplifier in the voltmeter. (15) (16)
2.3.2 Current generation
An alternating current source can be obtained by combining a voltage generator with a voltage‐
to‐current convertor circuit. For a current source, high output impedance is desired in EBI
measurement, especially in BIS where the working frequency goes up to several Mhz. However,
the output impedance of a current source drops as the frequency increases. This is caused by
the parasitic capacitances that come from many components in the circuit, for example between
electrodes. The output impedance of the current source should be at least 100 kOhm (17).
Sinusoidal signal generation
Sinusoidal signal can be generated from either analog or digital method.
8
One example of analog method is to use a sinusoidal oscillator that converts DC power to a
periodic waveform. This method requires complexity in circuits and high accuracy in some of
the electrical components. And it lacks flexibility compared to digital methods.
Generating waveforms with digital modules is called direct digital synthesis (DDS). The block
diagram below shows the idea of a simple DDS system (Figure 8) (18). DAC takes values from a
look‐up table where the address counter points. As the counter steps through the look‐up table
repeatedly, a periodical wave is obtained from the DAC output. The low‐pass filter (LPF) after
the DAC filters out the high‐frequency harmonics and makes the curve smoother.
VCCS
Many studies have been conducted on the VCCS design to achieve as large output impedance
at high frequencies as possible (17) (19). Some typical VCCS configurations include Howland
circuit, load‐in‐the‐loop circuit, etc. More detailed descriptions can be found in Section 3.3.1.
2.3.3 Impedance analyzing
One of the most popular methods for analyzing the impedance of biological material is the
quadrature demodulation (QD) method (20). The basic idea is introduced here.
Consider 0cos( )i t I t , by adding the phase shift caused by the impedance Z, the
expression of voltage can be written as:
0
0 0
( ) ( ) cos( )
= cos( )cos sin( )sin
v t Z i t I Z t
I Z t I Z t
, [6]
where the two items are in phase and in quadrature with the injected current. Then the
impedance Z can be expressed as:
cos sinZ R jX Z j Z [7]
In the upper branch, the voltage is multiplied by 0cos( )t , so the signal before low‐pass filter is:
1 0
0 0
0 0
( ) ( ) cos( )
cos( ) cos( )
1 cos(2 ) sin(2 ) ( cos sin )
2 2
v t v t t
I Z t t
t tI Z
[8]
The high frequency components are filtered out by the low‐pass filter, so the output contains
only 1
cos2
I Z which can be written as 2
IR . Similarly, the output of lower branch is
2
IX
Figure 8 Block diagram of a simple DDS system.
Address
counter Look‐up
table DAC LPF Register
fin Waveform
Figure 9 Quadrature demodulation method.
Other impedance analyzing methods include measuring the amplitude and phase using Gain‐
phase detector (21), bridge method (22), etc.
2.4 Communication protocol
Communication between devices requires a common language that could make data
identifiable. Communication protocols are such rules that define the formats of data and may
contain other information like the speed of transmission, the order of data bits, direction of
operation, etc.
2.4.1 I2C
Inter‐integrated circuit (I2C) is a multi‐master and multi‐slave protocol. It uses two bidirectional
signal lines. One is the serial data line (SDA) for data transmission, and the other is the serial
clock line (SCL) for two‐wire interface clock frequency.
Figure 10 I2C connection with one master and three slaves (23)
Data transmitted between master and slave device always begins with a START bit and ends
with a STOP bit. After the master device starts data transmission, the master device reaches to
each slave device with the slave’s unique address. If the address matches, the slave will respond
to the master with an AKCNOWLEDGE signal.
2.4.2 SPI
Serial peripheral interface (SPI) is a four‐wire full‐duplex interface allowing a single master to
communicate with one or multiple slaves. Master In Slave Out (MISO) is used for sending data
from slave to master. Master Out Slave In (MOSI) is used for sending data from master to slave
device. Serial Clock (SCK) is configured by the master device and is used to synchronize data
transmission. Slave Select (SS) is used to select the slave device that the master wants to
communicate with. MOSI, MISO and SCLK are common to all slave devices, while SS is specific
for each slave. The slave device is enabled only when its SS pin is low. See Figure 11.
10
Figure 11 SPI communication with single master and single slave (24)
2.4.3 I2C vs. SPI
Both I2C and SPI are commonly used in electronic devices. However, they have some important
differences that make them suitable for different purposes. Understanding the difference
between I2C and SPI helps to select a proper interface for certain project. Two aspects are
discussed below:
Wiring: I2C is a two‐wire interface, while SPI typically requires 3+N signal lines for N slave
devices.
Speed: I2C is slow compared to SPI. It transfers data at a speed of 100 kbps in standard mode, 400
kbps in fast mode, 1Mbps in fast mode plus and 3.4 Mbps in high‐speed mode (23). But high‐
speed mode is not always feasible because of limitations on the master side. SPI has no specific
working mode or any defined limit. The throughput rate varies from device to device, and can
go higher than 10 Mbps.
2.5 Arduino Uno
Aruidno Uno (Figure 12) is the latest revision of the basic Arduino USB board. It is based on the
microcontroller ATmega328. The system clock is 16 Mhz. The board has 14 digital input/output
pins and 6 analog inputs. Some of these pins have special functions for communicating with
other devices or microcontrollers. (25)
For SPI communication using SPI library:
Table 2 SPI pins on Arduino Uno
Pin 10 Slave selection (SS)
Pin 11 Master out slave in (MOSI)
Pin 12 Master in slave out (MISO)
Pin 13 Serial clock (SCK)
For I2C communication using Wire libray:
Table 3 I2C pins on Arduino Uno
Pin A4 Serial data (SDA)
Pin A5 Serial clock (SCL)
Arduino Uno could be programmed with Arduino software by simply connecting the board to
computer via USB port. Arduino boards come with an integrated development environment
(IDE) which is an open‐source software based on Processing, avr‐gcc, and other open source
software (26). The Arduino programs can be written in C/C++. Arduino itself has its own
standard library and some other libraries that have made some transforms on C/C++ language.
A typical Arduino program has two major functions: setup(), which runs in the beginning of a
program and initializes settings; and loop(), which is called repeatedly to fulfill desired tasks.
Figure 12 Arduino Uno front (25).
3 METHODS 3.1 System Implementation A simple impedance measurement system was implemented in this thesis. Arduino Uno was
used as a microcontroller. It wrote to a DAC and generated a sine waveform. A low‐pass filter
was connected to the DAC output to smooth the signal and a high‐pass filter was connected
after the low‐pass filter. The high‐pass filter was used to remove the DC component from DAC
output, since the output range of DAC used in the project was 0‐5V (27). The voltage source
would then be transferred to a current source after VCCS. A DC offset was added to the voltage
signal over the RC model to fit the analog input range of ADC. The ADC measured voltages
over the RC model and a reference resistor. Voltage data was then sent to Arduino Uno. Finally,
samples were sent to Matlab and impedance was calculated and displayed in Matlab. The block
diagram of major function blocks in the system is shown in Figure 13 below.
3.2 Source generation
3.2.1 Generating waveforms from look‐up table
A sinusoidal voltage signal was generated from DAC using the DDS method. To generate this
waveform, a sine wave look‐up table is needed. The look‐up table stores both amplitude and
phase information of a sine (or cosine) wave. When reading from the look‐up table
continuously, the index of the amplitude value increases and so does the phase of the output
waveform. To achieve n‐bit resolution, a sinusoidal cycle is divided into 2n phase points (Figure
14). If these points are read by DAC successively without skipping points, the frequency of the
output waveform obtained will be:
1
2out innf f [9]
Figure 13 Simplified block diagram of the impedance measurement system.
I
DC power supply
VCCS
Microcontroller
(Arduino Uno)
DAC ADC Matlab2R1C model V V
Samples
14
Figure 14 A sinusoidal cycle is divided into 2n points.
The frequency is changeable by changing the input clock frequency, rewriting the look‐up table
or skipping points.
In our project, the sine wave look‐up table was stored in the flash memory of Arduino. To
achieve the highest frequency, 32 points were taken for one sinusoidal cycle.
3.2.2 MCP4725
MCP4725 (27) is a single channel 12‐bit DAC supporting I2C interface. This chip is chosen
because it is easy to use. It has three modes: standard mode supports a baud rate of 100 kbps;
fast mode supports a baud rate of 400 kbps; high‐speed mode supports 3.4 Mbps. The
maximum SCL clock frequency supported by ATmega328 on the Arduino Uno board is 400
kHz (28). So it is only possible to use standard and fast mode with Arduino Uno.
Fast mode communication was used in the thesis to get as high speed as possible with available
hardware components. Commands that need to be written in the microcontroller are shown in
Figure 15.
The output voltage is given by:
4096REF n
OUT
V DV
[10]
where equals to the single power supply and is the input code. In our case, is
3.3 V from Arduino Uno board. The output signal ranges from 0 to 3.3 V. And the smallest
voltage difference that MCP4725 can produce is 0.8 mV.
Arduino Uno supports two‐wire interface communication with the wire library. Common
commands include: Wire.begin() to initiate the wire library, Wire.beginTransimmission(address) to
begin transmission to the I2C device with the given address, Wire.endTransmission() to end the
transmission and so forth. Detailed description and instruction for the library can be seen in (29).
Figure 15 Fast mode write command. (27)
3.3 VCCS
3.3.1 VCCS configurations
Load‐in‐the‐loop
A single operational amplifier (Op‐Amp) can work as a simple and effective VCCS. In a circuit
like Figure 16, if the Op‐Amp is ideal, the electrical current flowing through the load will be
equal to that in R1. The output current can be written as:
1
1load
VI
R [11]
which is independent of the load value.
Figure 16 Simple load‐in‐the‐loop circuit.
16
Seoane et al (30) proposed an enhanced version based on simple load‐in‐the‐loop configuration.
A current conveyor was added to the first stage so that the output current would be
independent of the value of resistor R3 that is connected to the inverting input of the second
stage. This resistor can be changed to get higher output impedance (Figure 17).
Figure 17 A single Op‐Amp VCCS circuit driven by current conveyor. (30)
Figure 18 shows a simplified equivalent schematic of AD844. The current flowing between the
input nodes gets replicated and flows in resistor Rt. In the method proposed by Seoane et al,
this current was connected to the next stage via AD844 Pin 5. The amplitude of current in
Figure 17 can be calculated approximately by:
1
1 IN
VI
R R
[12]
where the typical value of RIN is 50 Ohm (31)
Figure 18 Equivalent circuit of AD844. (31)
Enhanced Howland circuit
The enhanced Howland circuit has an advantage over other current source configurations: it
needs only one Op‐Amp and five resistors to work. The circuit is comparably simple. The
output current is given by:
3
4 2
inL
V RI
R R [13]
The resistance follows the ratio:
3 4 5
2 1
R R R
R R
[14]
Figure 19 Enhanced Howland circuit. (32)
DOA circuit
Double Op‐Amps are used in this circuit (32). It features a differential amplifier with a positive
feedback. Let . The output current is calculated by:
3
inL
VI
R [15]
Figure 20 DOA current source circuit. (32)
3.3.2 Measurement of output impedance
The output impedance was measured according to the schematic diagram shown in Figure 21.
Figure 21 Schematic diagram used to measure the output impedance. Adapted from (33).
The following equations can be written according to KCL and KVL.
When the switch S is closed:
1 1s zi i I [16]
18
1 1s z LZ i I R [17]
When the switch S is open:
2 2s zi i I [18]
2 2s z LZ i I P R [19]
Subtracting Equation [16] and [18]:
1 2 2 1z zI I i i I [20]
Subtracting Equation [17] and [19], and substituting with [20], can be calculated from
equation:
2 1 /s L LZ I P R I R I [21]
3.3.3 Simulation
Software environment
Three VCCS configurations: load‐in‐the‐loop circuit driven by a current conveyor; enhanced
Howland circuit and DOA circuit were simulated in Multisim. Multisim is a powerful
simulation environment developed by National Instruments. It has a large number of
components in the library, which makes it convenient to build a circuit, simulate it and monitor
the signals.
Besides the inbuilt modules like oscilloscope and multimeter, Multisim software offers two
convenient functions that analyse frequency response of a circuit:
AC analyse ‐ This function shows the value of chosen parameters over a range of frequencies.
Single frequency AC analysis ‐ This function shows the value of chosen parameters at a single
frequency. The user can choose either to display the result in real/imagery form or
magnitude/phase form.
Output impedance measurement
The output impedances were measured according to 3.3.2. P was set to 500 Ohm and RL was set
to 200 Ohm. The current flowing through the load was measured.
Output current measurement
The output currents were measured with a load of 470 Ohm. Then the values were normalized
by dividing the output current at the lowest frequency.
3.3.4 PCB prototyping
After simulation, the circuits were drawn in Eagle 7.1.0 (See Appendix A) and printed circuit
board (PCB) files were generated (See Appendix B) and sent to milling.
Boards were connected to power supply in the lab for testing. In consistence with steps in
simulation, the output currents of PCBs were measured with a load of 470 Ohm. Then values
were normalized by dividing the output current at the lowest frequency.
3.4 Signal measurement
3.4.1 Signal collection setup
Two voltage levels were measured with the setup shown in Figure 22. A reference resistor was
connected in series with the tested load. The voltage over the reference resistor is linear to its
current flow, so the phase information of electrical current was obtained. Signals went through
a voltage lifting circuit (34) before entering ADC to match the ADC’s analog input range.
Figure 22 Block diagram for signal measurement
3.4.2 MCP3008
MCP3008 (35) is an 8 channel 10‐bit ADC with SPI Serial Interface. It operates with a single
power supply ranging from 2.7 V to 5.5 V. The maximum sampling rate is 75 ksps at VDD = 2.7
V and 200 ksps at VDD = 5 V. According to Nyquist‐Shannon sampling theorem – the sampling
rate should be higher than twice the value of the maximum frequency in the signal to avoid
aliasing. Theoretically MCP3008 is able to sample 100 kHz signal at 5 V, which is not sufficient
for BIS measurement that deal with frequencies up to Mhz. However, because the signal
generated in this thesis is way below 100 kHz, MCP3008 is enough for signal sampling.
The timing chart of SPI communication with MCP3008 is shown in Figure 23. The ADC chip
works in mode (0,0), which means the base value of serial clock is low and data are sampled on
the rising edge of clock.
20
Figure 23 SPI Communication with the MCP3008 (Mode 0,0: SCLK idles low).
To get the SPI communication to work, the Arduino sends command bits to the ADC chip. This
configures the ADC chip to work in either single‐ended or pseudo‐differential input mode and
select channel for the analog input.
In single‐ended mode MCP3008 can measure analog inputs between 0 and VREF (3.3 V). And in
pseudo‐differential mode the IN‐ should be within (‐100 mV, 100mV), and IN+ should be within
(IN‐, VREF +IN‐). However in our case, the voltage to be measured was bipolar. So a voltage
lifting circuit was used before connecting to ADC.
Arduino has a SPI library to support the communication between Arduino and SPI devices.
Detailed information could be found in (36).
3.4.3 Communication between Arduino Uno and Matlab
Since Arduino Uno has no file system, it is impossible to save data using Arduino Uno alone.
Data processing is time consuming, so it is inefficient to do it in the Arduino sketch. Exporting
data to other software to save the file somewhere on the computer or process data and display
result is necessary. Matlab was chosen in this project for its convenience to communicate with
Arduino Uno.
Matlab is able to communicate with Arduino Uno in four different ways.
The first method is to use the Matlab Arduino Support package “Aruidno IO” that supports
serial port communication between Matlab and Arduino. This support package can be
downloaded from (37). It supports Arduino Uno, Mega 2560 and Duemilanove. The Aruidno IO
package provides a server sketch program that should run on Arduino. When the sketch is
uploaded to the Arduino board, board listens to the commands from serial port. There are also
a Matlab API and Matlab example files in the package. These files altogether allow users to
access and control pins on Arduino board from Matlab commands directly.
The second method is to use Simulink Arduino Support package (38). It contains common
function blocks like Analog I/O, Digital I/O, PWM, and also some function blocks for Ethernet
shield and WiFi shield. Users can connect these blocks with other existing blocks in Simulink,
modify the parameters and program the Arduino board without even write any command.
Figure 24 Arduino common blocks. (39)
The third method is to use Matlab serial port interface capability. It treats Arduino with no
difference from any other devices that want to send data to Matlab and do further data
processing in Matlab. Sketches that manipulate I/O pins are written with Arduino software and
uploaded to the board. In the Arduino software, a serial monitor takes and displays strings or
numbers from the serial port. Matlab can read from the serial port when the serial monitor is
closed and the serial port is not occupied.
The fourth method is to use Simulink to receive data from the serial port in real time. This is
achieved by using serial port interface blocks, such as Serial Receive, Serial Send, Query
Instrument and To Instrument.
In our project the command lines for controlling Arduino Uno board was written in Arduino
software. On the Matlab side, the codes created a serial port object and read data from the port.
3.5 Results display Arduino sends samples to the serial port. Matlab reads from the serial port and performs
further processing and calculations on the data.
3.5.1 Matlab GUI
Matlab offers a graphical user interface design environment (GUIDE) for designing graphical
user interface (GUI) (40). Users can add modules like toolbars, push buttons, and pop‐up menus
by simply clicking on their icons and put them to desired position. The tasks that need to be
implemented are defined with Matlab codes. For example, when a push button is clicked the
codes under its callback function are executed.
3.5.2 Impedance analysing
Samples collected in Matlab were fitted to the form: ( ) sin( )f t a b t c d [22]
using the least‐squares curve fitting function lsqcurvefit(). When the fitting curve is generated, it
is easy to compare the amplitude and phase information from the parameters in the function.
22
Since a reference resistor is connected in the circuit (Figure 22), and one of the channels
measures the voltage over both tested load and reference, the load value and reference resistor
follows the relation in Equation [23]:
signalLOAD REF
VZ R
I [23]
This equation can be extended assuming LOAD LOAD LOADZ R j X . The resistance and reactance
of the load can be calculated from:
2 2
1 2
( )/
tan( )
signal
REF LOAD
ref REF
REF LOAD
VR R X
V R
Xc c
R R
[24]
where |Vsignal| (a1), |Vref|(a2), c1, c2 are coefficients for the fitted curves.
4 RESULTS In this chapter the output of signal generation, VCCS and signal collection are presented.
4.1 Signal generation The voltage signal was generated with 12‐bit DAC chip MCP4725 (Figure 25.Channel 1). Angles
can be seen clearly on the waveform. An RC low‐pass filter was applied to the output signal to
attenuate high‐frequency harmonics from the waveform. After that, an RC high‐pass filter was
added to remove the DC offset. A smooth sinusoidal wave with around 3.3 Vpp was obtained.
The SCL signal frequency from Arduino was around 278kHz.
Figure 25 DAC output waveform (Channel 1, up) and waveform after low‐pass and high‐pass filtering
(Channel 2, down).
4.2 VCCS
The output impedance and output current of the three VCCS configurations at frequencies
1kHz, 10kHz, 50kHz, 100kHz, 300kHz, 1MHz and 2MHz were simulated in Multisim. PCB
prototypes were tested in lab.
4.2.1 Simulation
Output impedance
24
Figure 26 Simulation results of three VCCS configurations’ output impedance over frequency from 1kHz
to 2MHz.
Table 4 Output impedance of three VCCS configurations, simulation result.
Load‐in‐the‐loop
circuit driven by
current conveyor
Enhanced
Howland
Double
Operational
Amplifier
Frequency(Hz) Zout(Ω) Zout(Ω) Zout(Ω)
1k >1.0M >1.0M >1.0M
10k >1.0M >1.0M >1.0M
50k >1.0M >1.0M >1.0M
100k >1.0M >1.0M >1.0M
300k >1.0M >1.0M >1.0M
1M ‐ 235.0k 242.8k
2M ‐ 65.9k 63.0k
Figure 26 and Table 4 contains the output impedance of these three configurations from 1kHz to
2MHz in simulation. All circuits maintain high output impedance over a wide frequency range
and show variance as the frequency increases. At the highest frequency 2MHz, enhanced
Howland circuit and DOA circuit have output impedance around 60kOhm. The curve for load‐
in‐the‐loop circuit driven by current conveyor shows abnormal behavior compared to other two
circuits.
103
104
105
106
107
-4000
-2000
0
2000
4000
6000
8000
10000
12000
14000
16000
Frequency [Hz]
Out
put
impe
danc
e of
VC
CS
[kO
hm]
Enhanced Howland,simulationDOA,simulation
Load-in-the-loop circuit driven by current conveyor,simulation
Figure 27 Simulation results of three VCCS configurations’ output current over frequency from 1kHz to
2MHz.
Seeing from the output current results in Figure 27, the enhanced Howland circuit shows the
least variation at a very high frequency.
4.2.2 PCB
Boards for three VCCS configurations are shown in Figure 28, 29, 30. Components were
soldered in lab.
Figure 28 PCB for load‐in‐the‐loop circuit driven by current conveyor
Figure 29 PCB for enhanced Howland circuit
103
104
105
106
107
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0.98
1
1.02
Frequency [Hz]
Out
put
curr
ent
of V
CC
S/C
urre
nt@
low
est
freq
uenc
y
Enhanced Howland,simulationDOA,simulation
Load-in-the-loop circuit driven by current conveyor,simulation
26
Figure 30 PCB for double Op‐Amp circuit
Figure 31 PCB tested results of three VCCS configurations’ output current over frequency from 1kHz to
2MHz.
Curves in Figure 31 show output current results from testing PCB in lab. The curves have
fluctuations. This is partly due to some errors when reading amplitude values from the
oscilloscope. The amplitude values shown in the oscilloscope was not stable. The last two points
on the load‐in‐the‐loop circuit driven by current conveyor curve are inaccurate. Because at
1Mhz and 2Mhz frequencies, the output waveforms have distortion.
For current amplitude confirmation, DAC was connected to the DOA circuit. And the output of
DOA circuit was connected to a pure resistance load of 330 Ohm. The peak‐to‐peak value of
output current was around 1.6 mA.
103
104
105
106
107
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0.98
1
1.02
Frequency [Hz]
Out
put
curr
ent
of V
CC
S/C
urre
nt@
low
est
freq
uecy
Enhanced Howland,labDOA,lab
Load-in-the-loop circuit driven by current conveyor,lab
Figure 32 Waveform after high‐pass filter (Channel 1, up) and voltage over a 330 Ohm load (Channel 2,
down).
4.3 Signal measurement and display
The frequency generated from DAC was very low (below 10Hz) when working together with
ADC chip. So this part of test was conducted using signal generator in the lab as the input
voltage to VCCS. The input voltage was set to 200 Hz, 2.4 Vpp. VCCS output was then applied
to the load connected in series with a reference resistor (Figure 22). Samples were sent to
Channel 0 and Channel 1 of MCP3008.
In Matlab, a simple GUI was designed as is shown in Figure 33. When “Plot” is clicked, the
serial port opens. Matlab reads from the serial port and stores certain number of sample points
in a matrix. The number of samples can be changed from the code. These samples are plotted to
the GUI after finishing reading.
Figure 33 GUI interface in Matlab.
When the “Interpolate” button is clicked, samples are fitted to a sinusoidal wave using the least‐
square method and then are displayed in the GUI.
28
Before clicking the “Calculate” button, the value of reference resistor must be entered into the
software.
Figure 34 An example of impedance calculation.
Figure 34 shows the interpolation result and impedance analyzing result for two 330 Ohm
resisters connected in serials. However there is an obvious phase shift between two curves. This
phase can be used as a calibration parameter for the system.
A 2R1C model was tested (Figure 35). Results are presented in Figure 36 and Table5.
Figure 35 2R1C model.
Figure 36 Results for 2R1C model
Table 5 Resistance and reactance values of a
2R1C model
Resistance
(Ohm)
Reactance
(Ohm)
Theoretical 556 ‐0.85
Measured 719 ‐450
Calibrated 809 75
5 DISCUSSION 5.1 Impedance measurement system
Using a DAC device with I2C interface is not a good choice for projects that demand high
speeds. The microcontroller ATmega 328 on the Arduino Uno board supports a maximum
serial clock of 400 kHz for two‐wire interface. In principle, with DAC working on the fast mode,
the maximum sine frequency generated per second should be around 400000 (bits transferred
per second) / 29 (bits for one data points, including three bytes command and data, one start bit,
one stop bit and three acknowledge bits)/32 (data points in one sinusoidal cycle). The result is
around 4.3 kHz. However, in practice the frequency of voltage signal generated from MCP4725
could only go up to around 260 Hz. The serial clock was measured in lab to be around 278 kHz.
This serial clock frequency explains the reason for a maximum signal frequency of less than
300Hz in the real test.
Three VCCS configurations were simulated, tested and compared. For both enhanced Howland
circuit and Double Op‐Amp circuit, the symmetry of circuit components is expected to
contribute to higher output impedance. This lays demands on the accuracy of the resistors. In
the load‐in‐the‐loop circuit driven by a current conveyor, AD844 was used as the current
conveyor and LMH6655 was used as the amplifier in the second stage. According to Equation
[12], the output current could be regarded simply as the ratio between V1 and R1 when R1 is very
high compared to RIN (Figure 17). Increasing the value of the resistor R3 connected between Pin
5 of AD844 and inverting input of LMH6655 is considered to be beneficial to higher output
impedance according to the equation for output impedance in (30). When changing R3, the
linearity of the system should be closely monitored to get reliable results. In the lab test, the
value of R3 was set to 6.5kOhm as in (30), and the desired output current was 1mA, the voltage
level at Pin 5 of AD844 went up to around 6.5V. This requires the power supply of AD844 to be
higher than 6.5V. Otherwise the output waveform will be flat during certain part of a cycle. To
power up both AD844 and LMH6655, more power supplies were used in the load‐in‐the‐loop
circuit driven by a current conveyor compared to the other two configurations. Besides, the
simulation and lab test results for this method show abnormity at 1Mhz and 2Mhz. The output
impedance has an increase at very high frequencies in simulation, and waveforms have
distortion in the lab test. More reasonable simulation results could be found in (30).
The measurement used two single‐ended analog input channels of MCP3008. So the common
mode signal stayed in the input and could lead to inaccuracy in sampling. To eliminate or
reduce the effect of common mode signal in the input, pseudo‐differential mode input should
be tested in future experiment. In terms of sampling speed, the maximum sampling rate of
MCP3008 is 75ksps, which means it can sample 37.5 kHz sine wave according to Nyquist‐
Shannon sampling theorem. Two channels work alternately. This will reduce the sampling rate
to half. But even if there is a need to sample the signal at higher frequencies, undersampling
technique can be applied to recover the original signal.
The speed limitation of the measurement block is not limited by MCP3008, but by the serial
interface between Arduino and computer. The maximum port speed is 128000 bps. This means
128000 bits of information is sent in one second. For one byte data transmission, there are data
bits and also start bit, stop bit and possibly some other information included. In section 4.3, the
frequency of the input was 200Hz. Seven samples were sent per second to the computer in the
form “Channel0Value‐space‐Channel1Value” (i.e. “1 1”). The number of voltage levels received
by the computer is 2800 points per second.
30
The signal collection in Matlab is not stable. Reading from serial port is not always successfully
executed probably because that some data is missing in the transmission process. Before
deciding to use Matlab to interface with Arduino, Processing software was tried. Received data
had blank lines or half blank (i.e. “1 1” was sent but only ”1 ” was received).
The interpolation method used in impedance analysis is sometimes time consuming and
sometimes it exceeds the maximum evaluation values and ends without any optimum solution.
Besides, the performed interpolation result is easily influenced by the samples used. In the
result for 2R1C model measurement, the amplitude ratio between two channels of samples is
around 3.5, which is bigger than the expected ratio calculated from circuit theory. This is
possibly caused by parasitic capacitor over the reference resistor, or errors introduced from
voltage lifting circuits.
The phase shift in the test with two pure resistors as load was tried as a phase calibration option
in testing the 2R1C model. The reactance of the calibrated goes nearer to the calculated value,
however the resistance part separates farther. More tests should be done to draw a conclusion.
Measuring the amplitude and phase of signal to analyse the impedance is intuitive.
The whole system was tested on the breadboard. The analog modules on the breadboard
includes an RC low‐pass filter, an RC high‐pass filter, two voltage lifting circuits, a reference
resistor and a 2R1C model to be tested. All the jumpers together make the parasitic capacitor
even more complex and introduce larger errors to the system.
5.2 Safety considerations
For the safety of patients, the current from EBI measurement device injected to human body
should be bipolar with an average current 0. If an electric signal with DC offset is applied, there
will be electrons accumulated and may cause damage to living tissues.
The amplitude of the current should be as low as possible. Many research studies limit the
maximum current to 1mA, which is less than the threshold of perception.
Besides, problems may occur when the patient is using other medical device like implanted
cardiac defibrillator. No accident has been reported. However, attentions should be paid in
these situations.
The system developed in this project generates an electrical current with Imax = 0.8mA and it is
bipolar with no DC offset. The system requires improvements in many aspects to get satisfying
results. So it is currently not aimed towards real life applications, but for education and research
purpose only.
6 CONCLUSIONS The EBI measurement system was studied in this thesis work. A system using Arduino Uno to
generate sine wave from DAC MCP4725 and collect samples with DAC MCP3008 was tested.
Three different VCCS configurations were simulated and tested with PCB in practice. Finally, a
simple GUI was implemented in Matlab to display and process data. The system is still quite
preliminary. It fulfills most of the functions in an impedance analyzer but with poor
performance. Further improvements need to be done.
32
7 FUTURE WORK 7.1 Recommendation
One problem is related to the speed of signals generated in the system. One Arduino Uno alone
is not sufficient for controlling both DAC and ADC and transfer data at the same time.
Suggestions would be to use a higher speed microcontroller and high‐speed DAC and ADC
chips, for example AD5764 from Analog Devices. It is a 16‐bit high‐accuracy DAC compatible
with SPI interface. And for the measurement part, data acquisition devices can be considered
for fast data sampling.
To reduce the jumpers needed in the experiment setup, I would recommend using a DAC chip
with bipolar output and ADC with differential anolog inputs. In this way the parasitic
capacitance in the system will be reduced.
In a bioimpedance analysis system, it is not important to visualize data in real‐time. So it is
advisable to store data first and send the package to computer after signal collection.
The calculation steps for the impedance will be clearer if the voltage over the load can be
measured directly instead of calculating from the load and reference combination as was done
in this thesis. It is advisable to connect the voltage over the load to an instrumentation amplifier
before it goes to the ADC input.
For impedance analysis section, system design environment like Simulink and Labview could
be considered. Many analog and digital functional modules are available in the software. The
QD method, for example, can be tried in Simulink.
7.2 Future work
The bioimpedance measurement system in this thesis is only considered as a pilot study. As
readers can see from the results and discussion parts, there are needs for improvement from
many aspects. The goal is to implement a low‐cost bioimpedance measurement device
compared to those that are available on the market.
Apart from that, in future work, how to build a multi‐frequency current source, how to extract
signals from samples, how to design a multi‐channel system and how to fit the device to clinical
needs are problems to be considered.
8 EXPERIENCE GAINED Both hardware and software development are involved in this thesis project. This makes it
interesting however complex. Of course I learned a lot about hardware, interface between
devices and knowledge on this topic. But the points I want to stress is about something else.
The most important lesson I have learned from the project is time management. I have to admit
I did not do very well in time control. Some problems were related to external or unexpected
forces, for example shipment of the components, DAC board broken in the last month. But
more were caused by being unfamiliar with the contents and underestimating the time needed
for completing sub‐tasks. I will definitely start everything as early as possible for the tasks in
the future. And I think this applies for any project and every people.
And it is important to talk to supervisor or ask help from internet. When you stuck with some
problem for too long, this will save a lot of time.
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APPENDIX A: Schematic of VCCS
38
APPENDIX B: PCB layout
TRITA 2015:013
www.kth.se