Noise reduction in ecg by iir filters a comparative study

International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 4, July-August (2013), © IAEME
13
NOISE REDUCTION IN ECG BY IIR FILTERS: A COMPARATIVE
STUDY
Imteyaz Ahmad1
, F Ansari2
, U.K. Dey3
1
Dept of ECE , 2
Dept of Electrical Engg. , 3
Dept of Mining Engg.
BIT Sindri, Dhanbad-828123, Jharkhand, India
ABSTRACT
Background: In monitoring mode only two leads are used so that ECG waveform has large
R wave amplitude so lead II is chosen. The monitoring mode bandwidth is 0.5-50 Hz as only
rhythmic information is required. The present paper deals with the digital filtering method
to reduce noise artifacts in the ECG signal. 4th
order Butterworth, Chebyshev 1,
Chebyshev 2 and elliptic filters are used to reduce noise interference from ECG signals.
Method: ECG signal is taken from physionet database. A ECG signal (without noise) is
added with 50 Hz interference, base line wander noise of .15 Hz and high frequency noise of
150 Hz and processed by low pass filter of cutoff frequency of 50 Hz, High pass filter of
cutoff frequency of 0.5 Hz and notch filter of 3 dB stop band bandwidth 0.2(49.9–50.1) Hz.
The order of filter is taken as 4. In this paper 4th order Butterworth, Chebyshev 1, Chebyshev
2 and elliptic filters are applied on the noisy ECG signal. Simulation results are also shown.
Comparison of these filters are done. All the designs are implemented using MATLAB FDA
tool.
Result: Performance of filters are analyzed by comparing signal power before and after
filtration and distortion to ECG waveform. It is found that digital filters works satisfactory.
Conclusion: 4th
order Butterworth filter gives best performance as compared to others as it
introduces minimum distortion to ECG waveform.
Key Words: Electrocardiogram, Butterworth, Chebyshev, elliptic and notch Filter.
INTERNATIONAL JOURNAL OF ELECTRONICS AND
COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)
ISSN 0976 – 6464(Print)
ISSN 0976 – 6472(Online)
Volume 4, Issue 4, July-August, 2013, pp. 13-25
© IAEME: www.iaeme.com/ijecet.asp
Journal Impact Factor (2013): 5.8896 (Calculated by GISI)
www.jifactor.com
IJECET
© I A E M E

14
INTRODUCTION
The electrocardiogram is the graphic recording or display of time variant voltage
produced by the myocardium during Cardiac cycle. The electrocardiogram is used clinically
is diagnosing various diseases and conditions associated with the heart. It also serves as a
timing reference for other measurements.
Figure 1: ECG waveform
Engineers working in the medical profession are encouraged to learn as much as
possible about medical and hospital practices and in particular about physiology of human
body. It is only by gaining such an understanding that they can communicate intelligently
with medical professionals. This interaction between the two fields has led to the
development of sophisticated medical equipment and systems. In monitoring mode only two
leads are used so that ECG waveform has large R wave amplitude so lead II is chosen. The
monitoring mode bandwidth is 0.5-50 Hz as only rhythmic information is required. The
tracing of voltage difference at any two sites due to the electrical activity of the heart is called
a lead. Although two electrodes can be attached to any part of the body to lead the heart
current to the galvanometer, it is customary to make use of the forearms, the left leg and the
pericardium. Each chamber of the heart produces a characteristics electrocardiographic
pattern. Since the electrical potentials over the various areas of the heart differ, the recorded
tracing from each limb vary accordingly [1].

15
Figure 2: The Einthoven triangle for defining ECG lead
ECG measurements may be corrupted by many sorts of noise. The ones of primary
interest are:• Power line interference• Electrode contact noise• Motion artifacts• EMG
noise• Instrumentation noise These artifacts strongly affects the ST segment, degrades the
signal quality, frequency resolution, produces large amplitude signals in ECG that can
resemble PQRST waveforms and masks tiny features that are important for clinical
monitoring and diagnosis. Cancelation of these artifacts in ECG signals is an important task
for better diagnosis.
While designing the ECG amplifiers bandwidth requirements should be considered
[2]. Van Alste JA, van Eck W, Herrmann OE has proposed the linear filtering method
for base line wonder reduction [4]. The time varying filtering is also proposed by Sornmo
L. for the reduction of the baseline wonder [5]. For the baseline wander filter presented
is a linear phase high-pass filter having a cutoff frequency lower than the heart rate [6].
Alarcon G, Guy CN, Binnie CD has applied the recursive butterworth filter for
reducing the noise contaminations [7]. Choy TT, Leung PM, has developed notch filter
ECG signal since its analog version is difficult to design [8]. Gaydecki P. has
described a simple but highly integrated digital signal processing system for real time
filtering of biomedical signals. Filters are realized using a finite impulse response; no
phase distortion is introduced into the processed signals [9].McManus CD, Neubert K
D, Cramer E, has compared filtering methods for elimination of AC noise in
electrocardiograms[10]. Cramer E te.al has given global filtering approach in which
two different filters are designed and are compared for power line estimation and removal
in the ECG [11]. Electromyogram (EMG) artifacts often contaminate the electrocardiogram
(ECG). They are more difficult to suppress or eliminate, compared for example to the
power line interference, due to their random character and to the considerable
overlapping of the frequency spectra of ECG. For filtering of electromyogram signal from
the ECG signal Christov II, Daskalov IK has given the solution by designing Low
pass digital filter of 35 Hz cutoff frequency[12]. Mahesh S. Chavan, R.A. Agarwala,
M.D. Uplane has given a comparative study of Butterworth, chebyshev 1, chebyshev 2 and
elliptic filter and analyzed the performance by comparing signal power before and after
filtration[13]. In this paper filter performance based on time and frequency domain analysis
was done.

16
Input ECG: Input ECG
ECG signal is taken from physionet ECG database with sampling frequency of 500
Hz as shown below in Figure 3. A ECG signal (without noise) is added with 50 Hz
interference, base line wander noise of .15 Hz and high frequency noise of 150 Hz is shown
in Figure 4.
0 1 2 3 4 5 6 7 8 9 10
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Time(s)
Amplitude(mV)
Pure ECG
Figure 3: Input ECG signal with sampling frequency of 500 Hz
0 1 2 3 4 5 6 7 8 9 10
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Noisy ECG
Time(s)
Amplitude(mV)
Figure 4: Noisy ECG signal (contain 50 Hz interference, base line wander noise of 0.15 Hz
and high frequency noise of 150 Hz)
Design of low pass filter
In the present paper all design is performed using Matlab FDA tool. Figure 5
shows basic Matlab model used in the filtration of the noise in ECG. Time scopes are
configured to store up to 5000 ECG samples. The 4th
order Butterworth low pass filter has
cutoff frequency of 50 Hz for monitoring mode. The magnitude response is flat and all poles
are inside the unit circle so design filter is stable. The phase response is nonlinear and
impulse response decay with time as shown in Figure 6.

17
Figure 5: basic Matlab model used in the filtration of the power line noise in ECG
0 50 100 150 200
-120
-100
-80
-60
-40
-20
0
Frequency (Hz)
Magnitude(dB)
Magnitude Response (dB)
0 50 100 150 200
-6
-5
-4
-3
-2
-1
0
Frequency (Hz)
Phase(radians)
Phase Response
-1.5 -1 -0.5 0 0.5 1 1.5
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Real Part
ImaginaryPart
4
Pole/Zero Plot
0 10 20 30 40 50 60 70 80
-0.05
0
0.05
0.1
0.15
0.2
Time (mseconds)
Impulse Response
Amplitude
Figure 6: magnitude response, phase response, pole-zero diagram, impulse response, step
response of the Butterworth low pass filter with cutoff frequency of 50 Hz

18
Figure 7: time and frequency domain response of before and after filtration of low pass
Butterworth filter with cutoff frequency of 50 Hz

19
Design of High pass filter
The 4th
order Butterworth high pass filter has cutoff frequency of 0.5 Hz for
monitoring mode. The phase response is linear. Impulse response is 1 at t=0 and is 0 for rest
of time. Poles lies on unit circle of the z plane. Designed filter is stable.
Figure 8: the magnitude response, phase response, pole-zero diagram, impulse response of
the Butterworth high pass filter with cutoff frequency of 0.5 Hz
0 50 100 150 200
0
1
2
3
4
5
6
Frequency (Hz)
Phase(radians)
Phase Response
-1.5 -1 -0.5 0 0.5 1 1.5
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Real Part
ImaginaryPart
4
Pole/Zero Plot
0 1 2 3 4 5 6 7 8
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Time (seconds)
Impulse Response
Amplitude
0 50 100 150 200
-60
-50
-40
-30
-20
-10
0
Frequency (Hz)
Magnitude(dB)
Magnitude Response (dB)

20
Figure 9: time and frequency domain response of before and after filtration of high pass
Butterworth filter with cutoff frequency of 0.5 Hz
Design of Notch filter
3- dB stop band bandwidth and the order of the filter were defined to design the
Butterworth notch filter. In the present case, order of the filter is 4 and the 3- dB stop
band bandwidth of 0.2(49.9–50.1)Hz were considered. Figure 10 shows the magnitude ,
phase response pole-zero diagram, impulse response, step response of the Butterworth
notch filter with the 3- dB stop band bandwidth of .2(49.9–50.1). The magnitude response
shows sharp cutoff at 50 Hz. The phase response is nonlinear. All zeros lies on the unit circle.
The zeros are located at ±0.6 radians.

21
0 50 100 150 200
-40
-35
-30
-25
-20
-15
-10
-5
0
Frequency (Hz)
Magnitude(dB)
MagnitudeResponse (dB)
0 50 100 150 200
-3
-2
-1
0
1
2
3
Frequency (Hz)
Phase(radians)
Phase Response
-1.5 -1 -0.5 0 0.5 1 1.5
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Real Part
ImaginaryPart
2
2
Pole/Zero Plot
0 5 10 15 20
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Time (seconds)
Amplitude
Impulse Response
Figure 10: the magnitude response , phase response, pole-zero diagram, impulse response
of the Butterworth notch filter with the 3- dB stop band bandwidth of .2(49.9–50.1)

22
Figure 11: time and frequency domain response of before and after filtration of Butterworth
notch filter with 3- dB stop band bandwidth of .2(49.9–50.1) Hz
Simulation result
Butterworth Low pass filter
The time domain response shows that high frequency noise is considerably reduced
and amplitude of R wave is also reduced slightly. The frequency domain response shows that
high frequency noise is considerably reduced and ECG signal power before filtration of -
18.34 dB drops to -68.5 dB after filtration at 150 Hz as shown in Figure 7.

23
Butterworth High pass filter
The time domain response shows that low frequency noise i.e. baseline wander noise
is reduced to minimum. The frequency domain response shows that low frequency noise is
considerably reduced as shown in Figure 9.
Butterworth Notch filter
The time domain response shows that ECG noise at 50 Hz is effectively reduced.
From frequency domain response ,the ECG signal spectrum before and after Butterworth
notch filtering with the 3- dB stop band bandwidth of .2(49.9–50.1)Hz shows power
reduction from -18.145 dB to -37.05 dB as shown in Figure 11.
Figure 12: shows noisy ECG, pure ECG, output of 4th
order Butterworth filter
order Chebyshev 1 filter

24
order Chebyshev 2 filter
order elliptic filter
CONCLUSION
4th
order Butterworth, Chebyshev 1, Chebyshev 2 and elliptic filters were designed
for sampling frequency of 500Hz. It is observed from time domain analysis of Figure 12,
Figure 13, Figure 14, Figure 15 that PQRST distortion in ECG waveform is lowest in
Butterworth filter as compared to other filters. In case of Butterworth low pass filter the
frequency domain response shows that high frequency noise is considerably reduced and
ECG signal power before filtration of -18.34 dB drops to -68.5 dB after filtration at 150 Hz
as shown in Figure 7.After low pass filtering this signal is applied to Butterworth high pass
filter to reduce baseline wander. From time and frequency domain response it is observed that
baseline wander is completely removed as shown in Figure 9.After this ECG signal is applied
to Butterworth notch filter for reducing 50 Hz noise. From time and frequency domain
response it is observed that 50 Hz noise is completely removed as shown in Figure 11. It is
observed that the signal power at 50 Hz before filtration is -18.145dB and after
filtration power is reduced from-18.145 dB to –37.05 dB. Simulation result shows that
while filtering the noise in ECG the PQRST segment of the ECG signal is modified.

25
REFERENCES
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chapter 5, TMH, 2007
[2] Carr, J.J. and J.M. Brown, Introduction to Biomedical Equipment Technology.
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ed., 1998.
[3] John G. Webster, Encyclopedia of Medical Devices and Instrumentation.Vol. 2.
[4] Van Alste JA, van Eck W, Herrmann OE, “ECG baseline wander reduction
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[5] Sornmo L, “Time-varying digital filtering of ECG baseline wander”, MedBiol. Eng
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[6] De Pinto V,“Filters for the reduction of baseline wander and muscle artifact in
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[7] Alarcon G, Guy CN, Binnie CD, “A simple algorithm for a digital three pole
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[8] Choy TT, Leung PM, “Real time microprocessor-based 50 Hz notch filterfor ECG”,
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[9] Gaydecki P, “A real time programmable digital filter for biomedical signal
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[10] McManus CD, Neubert KD, Cramer E, “Characterization and elimination of AC
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[11] Cramer E, McManus CD, Neubert D, “Estimation and removal of powerline
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[12] Christov II, Daskalov IK, “Filtering of electromyogram artifacts from the
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