Download Non-invasive Bio-impedance Measurement Using Voltage

International Conference on Electrical, Electronics and Biomedical Engineering (ICEEBE'2012) Penang (Malaysia) May 19-20, 2012
Non-invasive Bio-impedance Measurement
Using Voltage-Current Pulse Technique
Sagar K. Dhar and Quazi D. Hossain
related to tissue structures and their physiological states and
functions is bioelectrical impedance, has been of significant
interest because of its several advantages such as
noninvasiveness, low cost, ease of application and capability
for online monitoring [2], [3] which measures the conductivity
and permittivity of bio-logical tissues changed directly or
indirectly by the measuring variable.
Abstract—Noninvasive detection is a fundamental prerequisite
for pervasive healthcare system and biosensing. Along with different
noninvasive techniques such as ultrasound, X-ray, magnetic
resonance and optical imaging, electrical impedance spectroscopy is
emerging as more suitable technique for tissue level diagnosis. This
paper presents a noninvasive technique for bioelectrical impedance
estimation by means of impedance spectroscopy applying voltagecurrent pulse technique and least square curve fitting method. Simple
circuit for current injection and voltage detection is presented with
common mode noise suppression circuit requires only two electrodes
would reduce problems due to electrode polarization. The current
source is presented with constant output current as low as 100 µA,
about 1MΩ load variation and 10 MHz mid-range bandwidth.
Voltage detection and impedance estimation is done with Data
Acquisition (DAQ) tool box of Matlab R2008a and curve fitting
technique. Successful simulation results in bioelectrical impedance
estimation are found with 1.5% maximum error; suggest impedance
measurement below 100 kHz because of higher response of
permittivity and conductivity of biological tissues in this band than
the high frequency band (MHz band).
The original bio-impedance technique was involved with
bioelectrical impedance analysis. Within a decade, this
technique is evolved into Bioelectrical Impedance
Spectroscopy (BIS) which is also called multiple frequency
bioelectrical impedance analysis. It enables to have an overall
figure of impedance which is of significant interest in
biomedical sensing for example, the tissue impedance at zero
frequency corresponding to extra-cellular resistance is useful
for the evaluation of mammary and lung cancers and fatty
tissues. BIS applies multiple frequency stimulation to measure
body impedance and study shows its viability for the
applications of body fluid measurement [4], [5] which
estimates extracellular fluid, intracellular fluid, and total body
water; also applicable for tissue volume change and tissue
characterization with impedance plethysmography [6]. It is
well known that the electrical properties of biological tissues
differ significantly depending on their structure and
characteristics [7]. Depending on such variation it is possible
to detect benign tissues with Electrical Impedance
Tomography (EIT). This has been reported by investigators
that electrical properties of tumors get changed significantly
and according to Fricke and Morse [8], tumor tissues show
higher permeability at 20 kHz compared to that of normal or
non-malignant tissues. Study shows that extracellular
resistance and intracellular resistance of cancer tissues are
significantly higher and plasma membrane capacitance is
significantly lower than normal tissues [9]. Similar results also
found by other investigations based on microwave bio-sensing.
Again, impedance measurement of bodily fluid such as saliva
and blood provides much fundamental information on
physiological state like glucose level and electrolyte
concentration. Study shows significant change in blood
conductivity and permittivity due to different level of glucose
[10]. Besides, any significant change in tissue characteristics
would be detectable with electrical impedance spectroscopy
and study shows its viability for visceral fat measurement [11],
prostate and lung cancer detection and bone fracture [12].
Keywords—bioelectrical impedance, impedance spectroscopy,
curve fitting, data acquisition tool box, non-invasive biosensing.
I. INTRODUCTION
P
healthcare system automatically calls for
intermittent, continuous or even contactless (wearable and
wireless) and distant biomedical sensing [1]. Such systems
not involve pathological patients only but also the healthy
people that for the sake of preventive measurement. Therefore,
an invasive sensor is not certainly going to be popular among
the healthy people. Besides, invasive sensing precludes
continuous monitoring and it is sometimes not possible for
specific cases (e.g. blood glucose monitoring) which inevitably
calls for noninvasive sensors. There are different popular
noninvasive techniques for bio-sensing like optical
spectroscopy, ultrasound, X-ray and magnetic resonance
imaging which typically measure the effect of absorption,
reflection or transmittance of non-ionizing radiation that
illuminates a portion of the subject. Such techniques offer
basic information on mass or proton density distribution. On
the other hand, one more technique that provides information
ERVASIVE
Sagar K. Dhar is with the Premier University, 1/A, O.R. Nizam Road,
Prabartak
Circle,
Panchlaish,
Chittagong,
Bangladesh
(phone:
8801818837084; e-mail: [email protected]).
Quazi D. Hossain is with Chittagong University of Engineering and
Technology, 163 Kaptai Road, Chittagong, Bangladesh (e-mail:
[email protected]).
Biomedical sensing which directly or indirectly related to
change in biological tissues, diagnosis based on bioelectrical
70
International Conference on Electrical, Electronics and Biomedical Engineering (ICEEBE'2012) Penang (Malaysia) May 19-20, 2012
impedance spectroscopy is emerging with greater prospects for
noninvasive bio-sensing than any other noninvasive
techniques. This paper presents bioelectrical impedance
measurement by means of voltage current pulse technique.
Bio-impedance parameters Re, Ri and Cm of electrical
equivalent circuit shown in Fig. 1 are estimated with least
square curve fitting method in Matlab 2008a. A current source
is designed with the option of setting any constant current
value as less as 100 µA, mid-range bandwidth of 10 MHz and
load variation up to 1 MΩ. Voltage detection is designed with
an instrumentation amplifier to provide good noise
performance and necessary signal gain along with parallel port
interfacing through Data Acquisition Toolbox of Matlab
R2008a.
Bioelectrical impedance in this paper is measured with
electrical impedance spectroscopy by means of voltage-current
pulse technique. Since, a discrete pulse contains all frequency
components, injection of a short duration current pulse would
provide complete frequency response of biological tissues. The
frequency behavior is detected by the distortion in voltage
pulse which is solely defined by the electrical behavior of
biological tissues and it is important to last the current pulse
duration until the resulting voltage is stable which practically
means that Cm has to be completely charged. The transfer
function of bioelectrical equivalent circuit is provided by (1)
and the change in pulse shape is shown in Fig. 2.
H ( s = jw ) =
II.METHODS
( R e + sR e R i Cm ) (1 + s ( R e + R i ) Cm )
(1)
When a current pulse is injected, the voltage across the
tissue would be V(t) = I(t)*h(t) where I(t)*h(t) represents the
convolution sum of time domain current, I(t) and the impulse
response of the bioelectrical equivalent circuit, h(t).
Consequently, the Fourier transform of V(t) will provide the
voltage transform V(s). So, once the time domain voltage V(t)
and current I(t) are acquired and are transformed to V(s) and
I(s), the impedance spectroscopy Z(s) is recovered by (2)
which represents both magnitude and phase of impedance
represented by (3) and (4).
The electrical equivalent circuit of biological cells is usually
represented with similar circuit shown in Fig. 1 which is
comprised of extra-cellular medium resistance, intra-cellular
medium resistance and cell membrane capacitance [13]. In
every case, subjected electrical current will flow through
biological cells or extra-cellular medium. Again, the current
through the cells may be classified as the current across the
trans-membrane ionic channel (shown as the path with Rm) or
across the plasma membrane. The cell membrane shows
dielectric property where the intra-cellular medium and
extracellular medium shows resistive behavior represented
with Re and Ri which consequently provides the capacitance
effect to plasma membrane represented with Cm. Due to the
very high trans-membrane channel resistance, it may be
ignored and the circuit is simplified with single extra-cellular
medium resistance Re, intra-cellular medium resistance Ri and
cell membrane capacitance Cm.
Z (s) = V (s) I (s)
Z ( w) =
(2)
2 ( R R )2
( Re + Re Ri ( Re + Ri ) w2Cm 2 )2 + w2Cm
e i
2
2
2
1 + ( Re + Ri ) w Cm

 ( w ) = − tan −1 
(3)
Re + Re Ri ( Re + Ri ) w 2 C 2 
 (4)
2
1 + ( Re + Ri ) w 2 Cm2 
wC m Re2
 1 + ( R + R )2 w2 C 2
e
i
m

(
)
Z ( w = 0 ) = max Z ( w ) = Re
(5)
Once impedance data is retrieved from frequency transform of
voltage and current pulse, it is enough either to work with
magnitude or phase to estimate Re, Ri and Cm. In this paper,
magnitude data of impedance is fitted with (2) by means of
least square method with iterated value of Ri and Cm where the
value of Re is directly calculated with (5).
Fig 2. Pulse response of bioelectrical circuit.
Fig 1. Electrical equivalent circuit of biological cells.
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International Conference on Electrical, Electronics and Biomedical Engineering (ICEEBE'2012) Penang (Malaysia) May 19-20, 2012
III. BIOIMPEDANCE MEASUREMENT SYSTEM
Impedance measurement is accomplished in two sections
comprising of current injection & voltage detection and
impedance estimation as shown in Fig. 3. The first section
involves two major hardware parts of impedance measurement
system: 1) current source and 2) voltage sensor. The second
section involves the software to transform the voltage and
current in frequency domain to estimate impedance
spectroscopy and impedance parameters Re, Ri and Cm
subsequently.
A. Current Pulse Generation
Current source is the most important part of bioelectrical
impedance measurement system and should have very good
stability in providing current irrespective to the load variation
and current value should be in 700 µA to 1mA [2]. Moreover,
the current source should have tuning option of both amplitude
and pulse width and invariable operation in low and high
frequencies simultaneously.
The constant current pulse in this paper is developed by
means of conversion of a voltage pulse which is generated
with the mono-stable operation of a 555 timer. Since, the
voltage pulse width is easily tunable in such operation; it in
other words provides the tuning of current pulse width. The
voltage pulse is then converted to constant current pulse
according to the circuit shown in Fig. 4. The current to load is
solely depended on RS, I = VIN/RS, and tunable as low as 100
µA. To meet up the stability as a current source against a wide
load variation, operational amplifier AD380JH is selected with
very high differential and common mode input impedance of
100 GΩ which makes the circuit applicable for constant
current source up to 1 MΩ as shown in Fig. 5. The frequency
response of the source in Fig. 6 reveals its mid-range
bandwidth as large as 10 MHz.
Fig 5. Variation of source current with Load.
Fig 6. Frequency response of current source.
B. Voltage Detection
Pulse based impedance measurement systems generally use
four electrodes [14]: two for current injection and two for
voltage detection. This paper presents only two electrode
arrangement for both current injection and voltage detection
shown in Fig. 7 which would reduce tissue irritation due to
polarization. Here, current is injected by the electrodes B and
A where the voltage is detected across electrode A and ground
which would be equivalent to voltage across A and B
according to the virtual ground phenomenon and makes
possible two electrode setup for voltage detection.
Re
Fig 3. Block diagram of bio-impedance measurement system.
Cm
Ri
B
A
Rlimit
5
Voltage 1 RS
Pulse
11
U1
3
AD380JH
9
4
10 2
Fig 4. Current pulse generation circuit.
8
Fig 7. Voltage detection with two electrodes.
72
International Conference on Electrical, Electronics and Biomedical Engineering (ICEEBE'2012) Penang (Malaysia) May 19-20, 2012
Biomedical sensors usually suffer from common mode noise
and to implement and manipulate bio-medical electrical signal
information, it is very important to deploy the front amplifier
with high common mode rejection ratio (CMRR) and high
differential gain. This paper presents the instrumentation
amplifier setup shown in Fig. 8 with the common mode
rejection performance shown in Fig. 9 where the gain ACL is
set at desired value according to (6). Finally, the voltage is
acquired with an ADC and parallel port interfacing by the
DAQ of Matlab R2008a for processing and estimation of
bioelectrical impedance parameters Re, Ri and Cm.
ACL = 1 + 2 R RG
(6)
C. Impedance Estimation
Once the potential across bio-logical tissues is fetched,
voltage spectrum is found using FFT in Matlab. By the same
procedure current spectrum is also found from known pulse
information and together with voltage and current spectrum,
impedance spectroscopy is found by (2). At this final point, the
magnitude of impedance spectrum data are calculated and
fitted to (3) to find impedance parameters Ri and Cm applying
least square method as shown in Fig. 10 and Re is directly
found by (5).
Fig 10. Curve fitting method.
IV. RESULT AND DISCUSSION
Electrical impedance is successfully estimated with around
1.5% maximum tolerance. The program of the impedance
parameter estimation is run in Matlab R2008a according to the
flow chart shown in Fig. 10. To test the accuracy of the curve
fitting algorithm, some predetermined value of Re, Ri and Cm
are set to create known impedance data and the outcome of the
program for Re, Ri and Cm are checked with predefined value.
Table I shows some instances of impedance parameter output
by the curve fitting program with error percentage. It is found
only 1.5% error in curve fitting method.
Fig 8. Common mode noise suppression circuit.
TABLE I
ESTIMATED IMPEDANCE PARAMETERS
Fig 9. Noise rejection with suppression circuit.
73
Re (Ω)
Err.
% Re
Ri (Ω)
Err. %
Ri
Cm (F)
Err. %
Cm
3.0000e+3
0
1000
0
8.005e-6
0.0625
5.0000e+3
0
2000
0
7.005e-6
0.0714
6.9999e+3
1.43
3000
0
5.985e-6
0.2500
8.9999e+3
0.01
4000
0
5.005e-6
0.1000
1.1000e+4
0
5010
0
4.005e-6
0.1250
1.3000e+4
0
6000
0
3.005e-6
0.1667
1.5000e+5
0.050
7000
0
2.007e-6
0.3500
International Conference on Electrical, Electronics and Biomedical Engineering (ICEEBE'2012) Penang (Malaysia) May 19-20, 2012
V.CONCLUSION
In the present work, stable current source and voltage
detection circuit with common mode noise suppression for
bioelectrical impedance measurement is presented.
Appropriate signal processing for impedance estimation from
impedance spectroscopy is modeled based on least square
curve fitting technique. Moreover, it is investigated that the
variation of bioelectrical impedance is higher in frequencies
less than 100 kHz for extra-cellular medium and plasma
membrane capacitance variation. Such findings along with
presented impedance measurement system would be applicable
for noninvasive bio-sensing based on bioelectrical impedance
spectroscopy.
ACKNOWLEDGMENT
The authors wish to acknowledge the invaluable
suggestions, support and resources by Dr. Sabuj Baran Dhar,
Assistant professor, Cox’s Bazar Medical College Hospital
and Mr. Tanzilur Rahman, Research Assistant, University of
Tokyo.
Variation of Cm
500
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