A New Approach for On-Line ECG Characterization

J. S. Sahambi S. N. Tandon R. K. P. Bhatt Electrical Engg., Center for Biomedical Engg., Electrical Engg.,

I. I. T. Delhi, Hauz Khas, New Delhi PIN 110 016

INDIA INDIA INDIA

I. I. T. Delhi, Hauz Khas, New Delhi PIN 110 016

I. I. T. Delhi, Hauz Khas, New Delhi PIN 110 016

Abstract - A new system has been developed for on-line processing of ECG. The Wavelet technique has been used for processing of electrocardiogram to provide a precise definition of timing intervals. Multiscale analysis by optimized wavelets combined with Digital Signal Processing (DSP) hardware and a PC results in a low cost system with on-line capabilities. The performance of the system was evaluated with MIT/BIH ECG data base and Standard CSE ECG library. The results indicate an accuracy of 95% in feature extraction in the presence of noise.

I. INTRODUCTION

The objective of the present research work is to use the state- of-art technology to develop a system for on-line timing characterization of ECG waveform. Digital Signal Processing (DSP) hardware as add-on card to PC (486) has been used to implement the wavelet technique.

The most common types of disturbances encountered in ECG processing are baseline drift and 50 Hz interference. The approaches reported for ECG timing characterization include the detection of onsets and offsets of the P and the T wave by the intersection of two lines representing the onsets and offsets [ l ] and length transform [2]. Both these techniques require special hardware and software to remove the noise prior to analysis. The results of these techniques indicate that there is appreciable error involved in the measurement of timing features in the presence of noise.

The wavelet technique takes care of noise due to its capabilities of analyzing the signal at various resolutions. The integral system, using DSP hardware and proposed optimized mother wavelet, has been used to determine the timing parameters of ECG waveform. It is important to evaluate the detection of onsets and offsets of the P and the T wave using a Standard CSE ECG Library and MIT BIH ECG database.

Wavelet transformation is a linear operation which decomposes a signal into components which appear at different scales (or resolutions) [3],[4],[5],[6]. The wavelet transform of a hnction f ( t ) E L2(R) at scale a and position z is given

by 0-7803-313 1-1/96$05.000 1996IEEE

where ‘Y(t) is the mother wavelet which should satisfy the admissibility conditions [6] and * denotes the complex conjugation. The mother wavelet and its scaled versions act as band pass filter on the signal. The wavelet we used is the first derivative of a smoothing function (gaussian function).

111. METHODOLOGY

The ECG is digitized at the rate of 250 samples per second with a 16 bit bipolar analog-to-digital converter with a dynamic range of -10 to +10 volts. The resolution of the system is 0.3 milli volts. The digitized data is then analyzed by the DSP card. The results of analysis are then given to the PC for display and storage.

A. Detection of onsets and offsets and width of the P and T waves using wavelets

The detection of onsets and offsets of the P and T waves is based on the modulus maxima and zero crossings of wavelet transform of the signal (ECG) in the characteristic scales[7],[8]. The wavelet transform is computed only for the scales of interest (Characteristic scales) which are chosen depending on the frequency content of the signal component to be analyzed and the pass band of wavelet filters. Cuiwei Li et.al., used the characteristic scale of z4 for analysis of the P and T waves (pass bands for four scales are given in Table 1). This is because the energies of the P and the T waves are in the range of 0.5 Hz and 10 Hz [9] and these frequencies are covered by scale z4.

The P wave generally corresponds to two modulus maxima (maxima and minima pair of wavelet transform) with zero crossing in between them[7]. The onset of the P wave is the onset of the maxima minima pair and offset of the P wave is the offset of the maxima and minima pair. They are detected by applying appropriate threshold to the wavelet transform[8]. From the onset and offset the width of the complex (P and T)is calcluated.

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B. Optimized mother wavelet

r_ 0

The pass bands of the wavelets used by Cuiwei Li et.al., are given in Table 1. It can be observed that the pass bands of scale z4 lies very close to zero and hence the results are affected by the low frequency disturbances like baseline drift. If the amount of low frequency noise is large, then one can think of using the scale 23. In this case the upper 3dB frequency is 27 Hz and it introduces errors due to high frequencies. Depending upon, whether the low frequency noise is dominant or high frequency, appropriate scale has to be used (which requires analysis on both the scales and hence more computations).

Therefore, in order to reduce the effect of low frequency and high frequency noise on the timing characterization a new mother wavelet (called optimized wavelet) with optimized pass band is proposed. The proposed mother wavelet is selected, such that, the pass band at scale 23 lies in between the pass bands of scale 23 and 24 of the un-optimized wavelet. The pass bands of four scales of the new wavelet are given in Table 1. The use of scale 23 of the optimized wavelet for the analysis of the P and the T waves gives less errors due to low frequency and high Wquency disfurbances. Analysis on only one scale also reduces the amoud of computations required. The errors in calculation of the P and the T width in un-optimized and optimized wavelet are depicted in Fig. 1 and Fig. 2.

With Un-optimized wavelet - With Opumized wavelet +

C. Application of DSP hara'ware

2' 22

The wavelet technique has been implemented on TMS 320C25 based add-on card and the other house keeping tasks like display and storage of results is done by a 486 PC. This combination makes the system on-line. The use of only one characteristic scale which requires less number of computations spares enough time to analyze the other ECG characteristic parameters.

freq. (Hz) freq. (Hz) freq. (Hz) freq. (Hz) 62 5 125.0 31.5 80 0 18.0 58.5 15.6 42.5

IV. RESULTS

2'

The performance of the system was tested on real ECG data from the Standard CSE ECG library. Figure 1 indicates the errors in detecting the onset and offset of the P and the T wave.

8 0 I 27.0 1 7.0 1 22.0

TABLE I PASS BANDS OF WAVELET FILTERS FOR UN-OPTIMIZED AND OPTIMIZED WAVELETS

AT FOUR SCALES ~~ 1 Un-optimized wavelet I Optimized wavelet

Scale I Lower3dB I Upper3dB I Lower3dB I Upper3dB

With Un-ophmrzed wavelet - With Optimized wavelet t

0 LOO 200 300 400 500 600 700 800 900 1000 Peak to Peak noise (micro volts)

Fig. 1. Magnitude of percentage error in calculation of P width with un- optimized and optimized wavelet as a function of noise.

Fig. 2. Magnitude of percentage error in calculation of the T width with un-optimized and optimized wavelet as a function of noise.

Its clear that the optimized wavelet gives higher accuracy and the system is faster (due to lower number of computations required).

V. CONCLUSIONS

A DSP based real time system has been developed for timing characterization (onsets and offsets) of the P and T waves of ECG using wavelet transforms. The use of proposed mother wavelet results in higher accuracy even in the presence of baseline wander and 50 Hz interference, in addition to reduction in computing time. The proposed integral system will be useful for high risk patients in coronary care units. The system is a table top model and can be moved easily to the patient site. The system has been implemented for one channel and can be modified for multi-channel analysis.

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