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Real time acquisition and analysis of ECG signal using MATLAB
Article · January 2010
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2. International Journal of Advances in Engineering Science and Technology 190
www.sestindia.org/volume-ijaest/ and www.ijaestonline.com ISSN: 2319-1120
ISSN: 2319-1120 /V2N2: 190-195 © IJAEST
Real Time Acquisition and Analysis of ECG signals
using MATLAB
RAMAN YADAV SHARDA VASHISTH* ASHOK K. SALHAN
EECE Department EECE Department Biomedical Instrumentation Division
ITM University, Gurgaon ITM University, Gurgaon Defence Institute of Physiology and
Haryana, India Haryana,India Allied Sciences DRDO, Delhi ,India
raman.y.90@gmail.com shardavashisth@itmindia.edu ashoksalhan@yahoo.com
* Corresponding Author
Abstract
The purpose of this paper is to design a portable, light weight ECG acquisition circuit for real time
monitoring of ECG of cardiac patients. The signal acquired from the body using acquisition circuit is then
displayed onto the computer using the sound port as a serial interface between circuit and PC. The real
time acquired signal is then analyzed using MATLAB. MATLAB program amplifies and filter the raw
ECG to eliminate noise added to the signal. It can further be used for identifying a number of diseases to
reduce the death rate due to heart diseases.
Keywords: ECG signal acquisition; MATLAB software; Sound Port;
I. INTRODUCTION
Now-a-days, heart diseases are a leading cause of death. According to World Health Organization (WHO)
estimation cardiovascular diseases are the main cause of death, nearly 17 million lives a year [1].
Healthcare for elder people has been the main focus of this proposed research. Electrocardiogram is the
signal of the heart muscles which are recorded from the body surface, to analyze any heart disease. It was
developed by William Einthoven in 1901, for which he was awarded the Nobel Prize in Medicine in 1924
[2]. A typical ECG signal for a normal heart beat is shown in Figure 1. Atria contraction gives the first
upward deflection P, and is known as atrial complex. Due to the action of ventricles, the other deflections
Q, R, S and T are observed and are known as the ventricular complexes [3]. Pressure exerted by heart
muscles in one pumping cycle gives the value of voltage. The voltage created in this process is of about 1
to 3mV. If the heartbeat moves up or down from the normal position then it shows abnormal rhythms
which may be caused due to a heart disease. These pathologic changes can be analyzed by ECG signal.
The changes can also be monitored using a handy ECG monitoring system [4].

3. IJAEST, Volume 2, Number 2
RAMAN YADAV et al.
ISSN: 2319-1120 /V2N2: 190-195 © IJAEST
Figure 1: A typical single ECG signal
Various bio-signals such as ECG, heart beat rate, blood pressure, blood oxygen saturation level, activity
signal such as acceleration and angular velocity are used for healthcare in daily life [5]. Analysis of ECG
is helpful in telemedicine and homecare. It helps in the reduction of relative expenses and hospital waiting
lists. But due to various factors faulty diagnoses may cause a risk to the patient’s health. So it needs a
qualified system and infrastructure with high efficiency [6]. Biomedical signals such as ECG, EMG, EEG
are very important in biomedical engineering and need real time monitoring, so a computer system plays
an important role for the various measurements and tests, with a better performance and lower cost [7].
Holter Monitoring system is non-invasive method which can be used to monitor ambulatory patient. ECG
signal can be acquired from the patient and then analyses and processing is done offline [8]. The acquired
signal is then interfaced with the computer using DAQ card. So needs DAQ card which further increase
the cost of the system and make the arrangement bulky. Most commonly used technique is Wilson
Central Terminal arrangement where ECG signal acquired using 3 electrodes [9]. Another system used is
Implantable Cardioverter Defibrillator (ICD) gives more accurate signal. But it is more expensive so used
only on the patient having high risk [10]. MOLEC monitor system acquires, analyzes, process and detect
abnormalities from the ECG signal in real time but requires analog to digital converter due to which cost
of the system increases [11]. Continuous monitoring of the ECG signal can be done using EPI-MEDIC
system which uses RS-232 port for computer interface [12]. Twelve lead are used to acquire ECG signal
which restricts the mobility of the patient. R –test is non-invasive method which continuously monitors
the signal for large interval of time. But the system is sensitive to interference can be easily corrupted due
to motion artifacts. Data can be transferred using sound card of PC which makes overall arrangement
convenient and effective.
In the present approach, the developed system comprises of electrodes, ECG acquisition circuit, a
computer system using the MATLAB software. The ECG signal acquired from the ECG acquisition
circuit is then fed to the sound port of the PC. The sound card of computer converts the analog signal
received into digital form and also amplifies the signal. MATLAB software [13, 14] program acquires
and filters the signal received from the sound port to remove the noise content added to the signal.

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Real Time Acquisition and Analysis of ECG signals using MATLAB
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II. MATERIALS AND METHODS
The analysis of ECG signal mainly involves the detection of QRS complex, P wave and T wave. The
ECG acquisition system consists of electrodes, amplifiers, filters to remove noise, and output display
device (Laptop/PC). The Functional block diagram of a Real time acquisition and transmission of ECG
signal is shown in figure 3.
A. ECG Acquisition
The main objective of the hardware circuit used is to acquire the ECG signal from the body surface. To
achieve this, the hardware acquisition unit is synchronized with MATLAB (matrix laboratory) software
for automatic data storage. The acquired signals are fed to ECG amplifier as these signals are in the range
of 1 to 3 mV so amplification of these weak signals is necessary. Output of the amplifier is then fed to
high pass filter and low pass filter circuit to filter the high and low frequency components and 50 Hz
power line interference from the acquired signal. The desired output from filter is then inputted into the
PC sound port. With the help of MATLAB program we recognize the ECG signal in the sound port of the
PC and then analyze the waveform obtained on the screen.
B. ECG Electrodes
Acquisition of ECG signal can be done with 3 or 6 or 12 electrodes. Here we propose to use 3 electrodes
to acquire ECG signal, two electrodes are placed on left and right wrist to provide positive and negative
connection. Ag/AgCl electrodes are used to pick the bio-potential signal from body surface and then to
convert them into a voltage signal. In AgCl electrodes, the sensors are of silver and coating of chloride
ions reduce skin impedance for perfect current flow [5]. The position of electrodes is set using the
Einthoven’s triangle. Figure 3 shows the diagram of Einthoven’s triangle for placement of electrodes on
body surface.
Figure 3: Einthoven’s Triangle
C. Front-end Amplifier:

5. IJAEST, Volume 2, Number 2
RAMAN YADAV et al.
ISSN: 2319-1120 /V2N2: 190-195 © IJAEST
An operational amplifier chip TL084C amplifies the ECG signal picked from the body surface. The OP-
AMP has a common mode rejection ratio (CMRR) of 86 dB and an adjustable gain of 500. Right leg
driven circuit is used to improve the CMRR of the circuit. Filter circuit is used to eliminate the noise
picked in this process. The ECG acquisition circuit uses 9 volts battery to eliminate the use of 230 V
power supply as the 230 V power supply is main source of noise in the circuit and also not safe to use for
measuring the signal.
D. Output Display Unit:
The output of the acquisition circuit is connected to the sound port of the interface unit (PC) and the
signal displayed using the MATLAB software. Sound port of PC provides the interface between the PC
and mobile phone. It makes the system cost effective and convenient, as there is no need of data
acquisition card for the interfacing between circuit and PC. Using a MATLAB program code, the PC can
recognize and display the ECG signal received at the sound port. The command “winsound” in MATLAB
is used to acquire the signal from the sound port and display on the screen. To minimize the noise content
from the real time acquired signal, FIR digital filter and band pass filter with pass band 0.05-150 Hz can
be used.
The subject was asked to sit comfortably on chair. The raw ECG signal was then acquired at normal
position. The signals received are then filtered using digital filters used in MATLAB program.
Figure 3: Functional diagram of ECG acquisition circuit
III. RESULTS AND DISCUSSIONS
Using ECG acquisition circuit we acquire signal at normal position. Figure 4 shows the raw ECG signal
acquired directly from the sound port of the PC and the filtered signal using digital filters in the
MATLAB coding displayed in figure 5. The code developed in MATLAB is capable of acquiring and
filtering raw ECG signal. Here MATLAB 7.5 (Release 2007b) is used for the real time acquisition and
filtering of raw ECG signal acquired. The frequencies of digital filters used are set accordingly to
acquire signal lies in the frequency range of 0.05-100 Hz. Here we are using sound port of the PC for

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Real Time Acquisition and Analysis of ECG signals using MATLAB
ISSN: 2319-1120 /V2N2: 190-195 © IJAEST
interfacing between PC and acquisition circuit so there is no additional requirement of DAQ card.
Effective signals can be acquired with proper selection and placement of electrodes. The Instrumentation
amplifier TL-084C is used to eliminate power line interference. An amplifier used amplifies the noise
signal added into the desired signal which can be minimized using analog filter.
Figure 4 Raw ECG acquired directly using sound port of PC
Figure 5 Filtered signal using digital filter in MATLAB program
IV. CONCLUSION
The rest ECG signal can be acquired easily using a single channel ECG amplifier. Any bio-medical
signals viz. ECG, EMG, EEG can be analyzed using this application software with proper selection of
amplification and filtering ranges. The signal acquired can be interfaced with PC using sound port so
there is no additional requirement of DAQ which makes the system cost effective. The system can be
extended and used with the standard 12 lead system for online diagnosis, analysis and distant monitoring
of bio medical signal. The system can be integrated with the wireless communication device like a
mobile phone so that telemonitoring can be made feasible and the data can be analyzed by cardiologist in
real time to reduce the trouble taken by patients to travel long distance. This is left as a future scope.
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