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International Journal of Electronics, Communication & Instrumentation Engineering Research and Development (IJECIERD) ISSN 2249-684X Vol. 3 Issue 3, Aug 2013, 65-74 © TJPRC Pvt. Ltd.

POWER LINE NOISE REDUCTION IN ECG BY BUTTERWORTH NOTCH FILTERS: A COMPARATIVE STUDY IMTEYAZ AHMAD1, F ANSARI2 & U. K. DEY3 1

Department of ECE, BIT Sindri, Dhanbad, Jharkhand, India

2

Department of Electrical Engineering, BIT Sindri, Dhanbad, Jharkhand, India 3

Department of Mining Engineering, BIT Sindri, Dhanbad, Jharkhand, India

ABSTRACT Background: The electrocardiogram has the considerable diagnostic significance, and applications of ECG monitoring are diverse and in wide use. Noises that commonly disturb the basic electrocardiogram are power line interference, instrumentation noise, external electromagnetic field interference, noise due to random body movements and respiration movements. These noises can be classified according to their frequency content. It is essential to reduce these disturbances in ECG signal to improve accuracy and reliability. The bandwidth of the noise overlaps that of wanted signals, so that simple filtering cannot sufficiently enhance the signal to noise ratio. The present paper deals with the digital filtering method to reduce 50 Hz power line noise artifacts in the ECG signal. 4th order Butterworth notch filters with different 3 dB stop band bandwidth is used to reduce 50 Hz power line noise interference from ECG signals. Method: ECG signal is taken from physionet database. A ECG signal (without noise) was mixed with constant 0.1 mVp-p 50 Hz interference and processed by notch filters of 3 dB stop band bandwidths: 48-52,49–51, 49.5–50.5, and 49.9–50.1 Hz. The order of filter is taken as 4. In this paper Butterworth notch filters are applied on the ECG signal(mixed with 50 Hz power line noise interference) with four different 3 dB stop band bandwidths: 48-52,49–51, 49.5–50.5, and 49.9–50.1 Simulation results are also shown. Comparison of these filters are done. All the designs are implemented using MATLAB FDA tool. Results: Performance of filters are analyzed by comparing signal power at 50 Hz before and after filtration and distortion to ECG waveform. It is found that digital filters works satisfactory. Conclusions: 4th order Butterworth notch filter with 3 dB stop band bandwidths of .2( 49.9–50.1) gives best performance as compared to others as it introduces minimum distortion to ECG waveform.

KEYWORDS: Electrocardiogram, Butterworth, Chebyshev, Elliptic and Notch Filter 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.


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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. 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] .

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


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Power Line Noise Reduction in ECG by Butterworth Notch Filters: A Comparative Study

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 effect of varying bandwidth of notch filters on their performance based on comparing signal power before and after filtration was done. 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) was mixed with constant 0.1 mVp-p 50Hz interference shown in Figure 4.

Figure 3: Input ECG Signal with Sampling Frequency of 500 Hz


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Figure 4: Noisy ECG Signal (Contain 50 Hz Power Line Noise) Design of Butterworth Notch Filters The Butterworth filter is the best compromise between attenuation and phase response. It has no ripple in the pass band or the stop band, and because of this is sometimes called a maximally flat filter. The Butterworth filter achieves its flatness at the expense of a relatively wide transition region from pass band to stop band, with average transient characteristics. A narrow-band band-reject filter will be referred to as a notch filter and the wideband bandreject filter will be referred to as band-reject filter. A notch (or band-reject) transfer function is:

There are three cases of the notch filter characteristics. These are illustrated in Figure (opposite). The relationship of the pole frequency, ω0, and the zero frequency, ωz, determines if the filter is a standard notch, a lowpass notch or a high-pass notch. If the zero frequency is equal to the pole frequency a standard notch exists. In this instance the zero lies on the jω-plane where the curve that defines the pole frequency intersects the axis. A low-pass notch occurs when the zero frequency is greater than the pole frequency. In this case ωz lies outside the curve of the pole frequencies. What this means in a practical sense is that the filter's response below ωz will be greater than the response above ωz. This results in an elliptical low-pass filter.

Figure 5: Types of Notch Filter


Power Line Noise Reduction in ECG by Butterworth Notch Filters: A Comparative Study

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In the present paper all design is performed using Matlab FDA tool. Figure 6 shows basic Matlab model used in the filtration of the power line noise in ECG.

Figure 6: Basic Matlab Model Used in the Filtration of the Power Line Noise in ECG 3- dB stopband 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 stopband bandwidth with different values( 4(48-52),2(49– 51),1(49.5–50.5), and .2(49.9–50.1) were considered.


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Figure 7: Shows the Magnitude, Phase Response Pole-Zero Diagram, Impulse Response, Step Response of the Butterworth Notch Filter with the 3- dB Stopband Bandwidth of .2(49.9–50.1)

SIMULATION RESULTS

Figure 8: Shows Noisy ECG, Pure ECG, Output of 4th order Butterworth Filter , Difference Between Processed ECG and Pure ECG with the 3- dB Stopband Bandwidth of .2(49.9–50.1) From the simulation it is evident that difference between processed ECG and pure ECG is minimum and power line noise interference is effectively reduced. ECG waveform is slightly distorted from 0 to 1 second and at the end.


Power Line Noise Reduction in ECG by Butterworth Notch Filters: A Comparative Study

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Figure 9: ECG Signal Spectrum before and after Butterworth Notch Filtering with the 3- dB Stopband Bandwidth of .2(49.9–50.1) From the ECG signal spectrum before and after Butterworth notch filtering with the 3- dB stopband bandwidth of .2(49.9–50.1) power reduction from -18.145 dB to -37.05 dB is achieved.

Figure 10: Shows Noisy ECG, Pure ECG, Output of 4th Order Butterworth Filter, Difference between Processed ECG and Pure ECG and ECG Signal Spectrum after Butterworth Notch Filtering with the 3- dB Stopband Bandwidth of 1(49.5–50.5)


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From the simulation it is evident that difference between processed ECG and pure ECG shows distortion in QRST segment of ECG waveform and power reduction from -18.145 dB to -70.025 dB is achieved.

Figure 11: Shows Noisy ECG, Pure ECG, Output of 4th Order Butterworth Filter, Difference between Processed ECG and Pure ECG and ECG Signal Spectrum after Butterworth Notch Filtering with the 3- dB Stopband Bandwidth of 2(49–51) From the simulation it is evident that difference between processed ECG and pure ECG shows distortion in QRST segment of ECG waveform and power reduction from -18.145 dB to -84.56 dB is achieved. Distortion in QRST segment of ECG waveform increases as 3- dB stopband bandwidth of the notch filter increases.


Power Line Noise Reduction in ECG by Butterworth Notch Filters: A Comparative Study

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Figure 12: Shows Noisy ECG, Pure ECG, Output of 4th Order Butterworth Filter, Difference between Processed ECG and Pure ECG and ECG Signal Spectrum after Butterworth Notch Filtering with the 3- dB Stopband Bandwidth of 4(48–52) From the simulation it is evident that difference between processed ECG and pure ECG shows distortion in QRST segment of ECG waveform and power reduction from -18.145 dB to -86.705 dB is achieved. Distortion in QRST segment of ECG waveform increases as 3- dB stopband bandwidth of the notch filter increases.

CONCLUSIONS Traditional analogue and digital filters are known to suppress ECG components near to the power-line frequency. Different 3- dB stopband bandwidth were defined to design the Butterworth notch filters with order of 4. These 3- dB stopband bandwidth are 4(48-52),2(49–51),1(49.5–50.5), and .2(49.9–50.1) Hz. These filters were designed for sampling frequency of 500Hz.When Butterworth filter was applied to ECG signal containing power line interference, from the frequency spectrum of the before filtration it is seen that the signal power at 50 Hz is 18.145dB.After filtration power is reduced from -18.145 dB to –37.05 dB with 3- dB stopband bandwidth of 0.2(49.9– 50.1) Hz. Simulation result shows that while filtering the power line interference the QRST segment of the ECG signal is modified. As the 3- dB stopband bandwidth of notch filter increases QRST segment of the ECG signal is more affected with distortion and power reduction increases. Distortion in QRST segment of ECG waveform increases as 3-


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dB stopband bandwidth of the notch filter increases. 4th order Butterworth notch filter with 3 dB stop band bandwidths of .2( 49.9–50.1) gives best performance as QRST segment of the ECG signal is less modified compared to others.

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Khandpur, R.S., Biomedical Recorders, Handbook of Biomedical Instrumentation, chapter 5, TMH, 2007

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Carr, J.J. and J.M. Brown, Introduction to Biomedical Equipment Technology. Prentice Hall, Inc., 3rd ed., 1998.

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John G. Webster, Encyclopedia of Medical Devices and Instrumentation.Vol. 2.

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Van Alste JA, van Eck W, Herrmann OE, “ECG baseline wander reduction using linear phase filters”, Comput. Biomed Res. 1986 Oct;19(5):417-27.

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Sornmo L, “Time-varying digital filtering of ECG baseline wander”, MedBiol. Eng Comput. 1993 Sep; 31(5):503-8.

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De Pinto V,“Filters for the reduction of baseline wander and muscle artifact in the ECG”, J Electrocardiol. 1992; 25 Suppl: 40-8.

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Alarcon G, Guy CN, Binnie CD, “A simple algorithm for a digital threepole Butterworth filter of arbitrary cutoff frequency: application to digital electroencephalography”, J Neurosci Methods. 2000 Dec 15;104(1):35-44.

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Choy TT, Leung PM, “Real time microprocessor-based 50 Hz notch filterfor ECG”, J Biomed Eng. 1988 May;10(3):285-8.

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Gaydecki P, “A real time programmable digital filter for biomedical signal enhancement incorporating a highlevel design interface”,Physiol. Meas. 2000 Feb; 21(1):187-96.

10. McManus CD, Neubert KD, Cramer E, “Characterization and elimination of AC noise in electrocardiograms: a comparison of digital filtering methods”, Comput Biomed Res. 1993 Feb;26(1):48-67. 11. Cramer E, McManus CD, Neubert D, “Estimation and removal of powerline interference in the electrocardiogram: a comparison of digital approaches”, Comput Biomed Res. 1987 Feb;20(1):12-28. 12. Christov II, Daskalov IK, “Filtering of electromyogram artifacts from the electrocardiogram,” Med. Eng. Phys. 1999Dec; 21(10):731-6. 13. Mahesh S. Chavan, R.A. Agarwala, M.D. Uplane, “ Comparative Study of Chebyshev I and Chebyshev II Filter used For Noise Reduction in ECG Signal” , International Journal of Circuits, Systems and Signal Processing Issue 1, Volume 2, 2008 14. www.physionet.org/physiobank/database/#ecg


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