Download A PC Based Biological Signal Monitor Using NI

R. Hanuma Naik et al. / IJAIR
ISSN: 2278-7844
A PC Based Biological Signal Monitor Using
NI-ELIVIS and Lab VIEW
R. Hanuma Naik, Dr.K.Muralidhara Reddy, Dr.B.Polaiah, A.Chakravarthi
Abstract:
A Biological signal is generated by various
physiological processes in human body. Acquisition of these
signals by conventional bio methods is very difficult due to lot of
noise interference. Signal processing is a huge challenge as the
actual signal strength is very low. These difficulties can be
overcome by using some user friendly platforms like Lab VIEW
from National Instruments. This paper deals with the real time
ECG signal acquisition from human body and filtering it
through digital and analog filters using Lab VIEW, NI ELIVIS
and also we simulated EEG and EMG signals on the Lab VIEW
platform.
Key words: ECG, EEG, EMG, NI-ELIVIS, Lab VIEW, Signal
processing.
In the man–instrument system, each transducer is
used to produce an electric signal that is an analog of the
phenomenon being measured. Signal conditioning equipment
is also used to combine or relate the outputs of two or more
transducers.
In the man-instrumentation system, the display
equipment may include a graphic pen recorder that produces
a permanent record of data. It is often necessary, or at least
desirable, to record the measured information for possible
later use or to transmit it from one location to another,
whether across the hall of the hospital or half way around the
world.
I.INTRODUCTION
Science has progressed through many gradual
states. It is a long time since Archimedes and his Greek
contemporaries started down the path of scientific
discoveries, but a technological historian could easily trace
the trends through the centuries. Engineering has emerged out
the roots of science, and since the Industrial Revolution the
profession has grown rapidly. Again, there are definite stages
that can be traced.
II. CARDIOVASCULAR SYSTEM
Fig.2. Cardiovascular System
Fig.1. Man-Instrumentation System
A block diagram of man instrumentation [1] system
is shown in the above fig.1. The basic components of this
system are essentially the same as in any instrumentation
system. The only real difference is in having a living human
being as the subject. The system components are given
below. The subject is the human being on whom the
measurements are made, since it is the subject who makes
this different from other instrumentation systems.
In many measurements, the response to some form
of external stimulus required. The stimulus may be visual,
auditory, tactile, or direct electrical stimulation of some part
of the nervous system.
Measurements can be made at various levels of
man’s hierarchy [2-3] of organization. The functional systems
can be broken down subsystems and organs, which can be
further sub divided into smaller and smaller units. The
process can continue down to the cellular level and perhaps
even to the molecular level. The major goal of biomedical
instrumentation is to make possible the measurement of
information communicated by these various elements.
Laplace equation may then be solved to give the potential
distribution [4] on the torso as
𝑐𝑜𝑠𝜃 𝑡 3𝑀 𝑡
∅ 𝑡 =
(1)
4𝜋𝜎𝑅2
© 2012 IJAIR. ALL RIGHTS RESERVED
161
R. Hanuma Naik et al. / IJAIR
Where, M(t) is heart vector, R is spherical conductor radius
and σ is the conductivity.
ISSN: 2278-7844
C. Cardiac muscle cell
III. MONITORING OF BIOLOGICAL SIGNALS
The biological signals involved in our present work
are ECG (ELECTRO CARDIOGRAM), EEG (ELECTRO
ENCEPHALOGRAP), and EMG (ELECTRO -MYOGRAM)
A. Electro cardiogram
The electrocardiogram (ECG) is a technique of
recording bioelectric currents generated by the heart [5].
These are the bio-potentials generated by the muscles of the
heart. Clinicians can evaluate the conditions of a patient's
heart from the ECG and perform further diagnosis [6-7]. ECG
records are obtained by sampling the bioelectric currents
sensed by several electrodes, known as leads. A typical onecycle ECG tracing is shown in below Fig.3.
Fig.3 A one cycle ECG
B. Anatomy of heart
It is really nothing more than a pump, composed of
muscle which pumps blood throughout the body, beating
approximately 72 times per minute of our lives. The heart
pumps the blood, which carries all the vital materials which
help our bodies function and removes the waste products that
we do not need [8-9].
The walls of the heart are made up of three layers,
while the cavity is divided into four parts. There are two
upper chambers, called the right and left atria, and two lower
chambers, called the right and left ventricles. The Right
Atrium, as it is called, receives blood from the upper and
lower body through the superior vena cava and the inferior
vena cava, respectively, and from the heart muscle [10] itself
through the coronary sinus.
Fig.4.Cardiac muscle
Each mechanical heartbeat is triggered by an action
potential which originates from a rhythmic pacemaker within
the heart and is conducted rapidly throughout the organ to
produce a coordinated contraction. As with other electrically
active tissues (e.g., nerves and skeletal muscle), the
myocardial cell at rest has a typical Trans membrane
potential, Vm, of about −80 to −90 mV with respect to
surrounding extracellular fluid.
D. Conduction system of the heart
Located in the right atrium at the superior vena cava
is the sinus node (senatorial or SA node) which consists of
specialized muscle cells [11]. The SA nodal cells are selfexcitatory, pacemaker cells. They generate an action potential
at the rate of (about 60 to 100 beats per minute), from the
sinus node, activation propagates throughout the atria, but
cannot propagate directly across the boundary between atria
and ventricles .The atrioventricular node (AV node) is
located at the boundary between the atria and ventricles; it
has an intrinsic frequency of (about 40 to 50 beats per
minute). However, if the AV node is triggered with a higher
pulse frequency, it follows this higher frequency. In a normal
heart, the AV node provides the only conducting path from
the atria to the ventricles. Thus, under normal conditions, the
latter can be excited only by pulses that propagate through it.
E. Cardiac wave form
An electrocardiogram — abbreviated as EKG or
ECG — is a test that measures the electrical activity of the
heartbeat. With each beat, an electrical impulse (or ―wave‖)
travels through the heart [12]. This wave causes the muscle to
squeeze and pump blood from the heart. A normal heartbeat
on ECG will show the timing of the top and lower chambers.
F.ECG leads
There are two types of leads—unipolar and bipolar. The
former have an indifferent electrode at the center of the
Einthoven’s triangle at zero potential. The direction of these
leads is from the ―center‖ of the heart radically outward and
includes the pericardial (chest) leads and limb leads— VL,
VR, & VF [1].
© 2012 IJAIR. ALL RIGHTS RESERVED
162
R. Hanuma Naik et al. / IJAIR

Lead I am a dipole with the negative (white) electrode
on the right arm and the positive (black) electrode on
the left arm.
ISSN: 2278-7844
The AD620 gain is resistor-programmed by R3, or
more precisely, by whatever impedance appears between Pins
1 and 8. The AD620 is designed to offer accurate gains using
0.1% to 1% resistors. Table 5 shows required values of R 3 for
various gains. Note that for G = 1, the R3 pins are
unconnected (RG = ∞). For any arbitrary gain, R3 can be
calculated by using the formula:
49.4kΩ
+1=G
R3
Fig.5 Lead Configuration
IV. HARDWARE IMPLEMENTATION OF ECG
A. Proposed structure:
Fig.6 Block Diagram of proposed structure
(2)
To minimize gain error, avoid high parasitic resistance in
series with R3.
Signal filtering is necessary to help isolate the
frequencies found in the ECG signal from the noise. With a
three lead system, the majority of the noise comes from the
electrical activity in the muscles on the arm, or
electromyography (EMG) noise. EMG signals are present in
a wide frequency band which overlaps with the ECG signal in
the lower frequencies.
B. Analog band pass filter design
The first stage of filtering is an analog filter. It is a
band pass filter with cut-off frequencies of 0.5 and 150 Hz.
This will help eliminate the high frequency noise from the
muscles before the signal is greatly amplified.
Fig. 9: Analog Band Pass Filter
Fig.7 Circuit Diagram of proposed structure
Fig.8. Experimental Setup.
C. Lab VIEW and NI-ELIVIS
The National Instruments Educational Laboratory Virtual
Instrumentation Suite (NI ELVIS) delivers hands-on lab
experience with an integrated suite of more than 12 of the
most commonly used instruments in one compact form factor
specifically designed for education. Based on industrystandard NI Lab VIEW [13] graphical system design
software, NI ELVIS, with powerful data acquisition and USB
plug-and-play capabilities, offers the flexibility of virtual
instrumentation and allows for quick and easy measurement
acquisition and instrumentation across multiple disciplines.
D. Digital filters using Lab VIEW
Once the signal has been acquired by the DAQ
Assistant into Lab VIEW, it is processed by two additional
filters and amplification of 100 times. The first filter is a band
stop filter between 55 and 65 Hz to eliminate power line
interference. A third order Butterworth (IIR) was used to
© 2012 IJAIR. ALL RIGHTS RESERVED
163
R. Hanuma Naik et al. / IJAIR
ISSN: 2278-7844
implement this filter because it is low order and has a good
frequency response for this signal.
The second is a tenth order Butterworth low pass
filter. The cut of frequency of this filter is 80 Hz to further
eliminate EMG noise. The ECG signal is located between 0.5
Hz and about 70-80 Hz depending on the individual.
Fig. 11 Raw ECG Signal
Fig.10 Lab VIEW code
VI. EEG AND EMG
Electroencephalography is a medical imaging
technique that reads scalp electrical activity generated by
brain structures. The EEG is defined as electrical activity of
an alternating type recorded from the scalp surface after
being picked up by metal electrodes and conductive media.
When brain cells (neurons) are activated, local
current flows are produced [4-15]. EEG measures mostly the
currents that flow during synaptic excitations of the dendrites
of many pyramidal neurons in the cerebral cortex.
Differences of electrical potentials are caused by summed
postsynaptic graded potentials from pyramidal cells that
create electrical dipoles between soma (body of neuron) and
apical dendrites (neural branches). Brain electrical current
consists mostly of Na+, K+, Ca++, and Cl- ions that are
pumped through channels in neuron membranes in the
direction governed by membrane potential.
The bioelectric potentials associated with muscle
activity constitute the Electromyogram, abbreviated as EMG.
An electromyography detects the electrical potential
generated by muscle cells when these cells are electrically or
neurologically activated. The signals can be analyzed to
detect medical abnormalities, activation level, and
recruitment order or to analyze the biomechanics of human or
animal movement.
The action potentials are about 100mV but due to
layers of connective tissues and skin, it is a complex signal
with less amplitude
Fig. 12 Final ECG SIGNAL
Fig. 13.EEG Simulation signal
VII. RESULTS
Care should be taken while measuring the ECG
from the patient, such as isolation from other persons and
electronic devices around him. The below image represents
the raw ECG signal acquired from the patient.
Fig.14. EMG Simulation Signal
© 2012 IJAIR. ALL RIGHTS RESERVED
164
R. Hanuma Naik et al. / IJAIR
VIII. CONCLUSION
The science of Biological signal processing is
vast and signal processing techniques involves lot of
mathematical modeling and hence adaptive filter techniques
are to be followed for further noise elimination. The proposed
method of ECG signal acquisition from LEAD I
configuration have produced some resultant waves which are
yet to be processed for further filtering process.
REFERENCES
[1] Biomedical Instrumentation and Measurements – by Leslie
Cromwell, F.J.Weibell, E.A. Pfeiffer, PHI.
[2] Principles of Medical Imaging, K.Kirk Shung, Benjamin Tsui
and Michael. B. Smith, Academic Press Inc., New York.
[3] Medical Instrumentation, Application and Design – by John G.
Webster, John Wiley.
[4] Principles of Applied Biomedical Instrumentation – by L.A.
Geoddes and L.E.Baker, John Wiley and Sons.
[5] Introduction to Biomedical Equipment Technology, Joseph J
Carr, John M.Brown, 4th Edition Pearson Education, Singapore,
2001.
[6] Marriott, H. J. L., Emergency Electrocardiography, Naples:
Trinity Press, 1997.
[7] Furlanello F, Galanti G, Manetti P, et al. Microvolt T-wave
alternans as predictor of electrophysiological testing results in
professional competitive athletes. Ann Noninvasive Electrocardiol
2004;9:1–6.
[8] Human physiology: from cells to system- by Lauralee Sherwood,
6th edition, Thomson Brooks/Cole.
[9] Mark, R. G., HST.542J/2.792J/BE.371J/6.022J Quantitative
Physiology: Organ Transport Systems, Lecture notes from
HST/MIT Open Courseware 2004, available at http://
ocw.mit.edu/OcwWeb/Health-Sciences-and-Technology/HST542JSpring-2004/.
[10] Stein PK, Reddy A. Nonlinear heart rate variability and risk
stratification in cardiovascular disease Ind. Pacing and
Electrophysiology. J. 2005;5:210–220.
[11] Katz, A. M., Physiology of the Heart, 4th ed., Philadelphia, PA:
Lippincott Williams & Wilkins, 2006.
[12] Fletcher, G. F., et al., ―Exercise Standards; A Statement for
Healthcare Professionals from the American Heart Association,‖
Circulation, Vol. 91, 2001, p. 580.
[13] Falcon, J.S. “LabVIEW State Diagram Toolkit for the Design
and Implementation of Discrete-Event Systems‖, 2006 8th
International Workshop on 10-12 July 2006 Page(s):469 – 470.
[14] McLaughlin MG, Zimetbaum PJ. Electrocardiographic
predictors of arrhythmic death. Ann Noninvasive Electrocardiol
2006;11:327–337.
[15] Martinez JP, Olmos S, Laguna P: Evaluation of a waveletbased ECG waveform detector on the QT database. Computers in
Cardiology 2000:81-84.
ISSN: 2278-7844
About the Author:
Hanuma Naik.R. is working as Assistant Professor at Rajeev Gandhi
Memorial College of Engineering and Technology, Nandyal, AP. He has
received B.E. Degree in Electronics and Instrumentation from Andhra
University and M.Tech in Control Engineering from Jawaharlal Nehru
Technological University, Anantapur. His main research interest includes
measurements, Process Instrumentation and Control System. He has
published articles in national and international conferences as well as
Journals.
Dr.K.Muralidhara Reddy is with the Department of Electronics and
Instrumentation Engineering of Rajeev Gandhi Memorial College of
Engineering and Technology, Nandyal, AP. He has awarded Ph.D. in 2008
from Sri Krishna Devaraya University, Anantapur.
Dr.B.Polaiah. is with the Department of Electronics and Instrumentation
Engineering of Sri Vidyanikethan college of Engineering, Tirupathi AP. He
has awarded Ph.D. from JNTU, Hyderabad
A.Chakravarthi. is with the Department of Applied Electronics and
Instrumentation Engineering of Sri GPR polytechnic, Kurnool, AP. He has
received M.Tech from Jawaharlal Nehru Technological University,
Kakinada.
© 2012 IJAIR. ALL RIGHTS RESERVED
165