Abstract
Electrocardiography (ECG) is the method of recording electrical activity of the heart by using electrodes. In ambulatory and continuous monitoring of ECG, the data that need to be handled is huge. Hence we require an efficient compression technique. The data also must retain the clinically important features after compression. For most of the signals, the low frequency component is considered as most important part of the signal. In wavelet analysis, the approximation coefficients are the low frequency components of the signal. The detail coefficients are the high frequency components of the signal. Most of the time the detail coefficients (high frequency components) are not considered. In this paper, we propose to use detail coefficients of Wavelet transform for ECG signal compression. The Compression Ratio (CR) of both the approximation and detail coefficients are compared. Threshold based technique is adopted. The Threshold value helps to remove the coefficients below the set threshold value of coefficients. Experiment is carried out using different types of Wavelet transforms. MIT BIH ECG data base is used for experimentation. MATLAB tool is used for simulation purpose. The novelty of the method is that the CR achieved by detail coefficients is better. CR of about 88% is achieved using Sym3 Wavelet. The performance measure of the reconstructed signal is carried out by PRD.
Highlights
ECG is used as an important signal which gives information about health of the heart
The methodology used in our research to investigate the usefulness of detail coefficients has given better results
The results show that the compression of ECG signal is possible using detail coefficients
Summary
ECG is used as an important signal which gives information about health of the heart. Due to continuous monitoring of ECG signals in 24 hour monitoring system and in ambulatory system, the data storage requirement increases. This in turn increases the storage cost. Instead of transmitting the stored data directly, ECG signal is compressed before transmission through common communication channels like phone line or mobile channel. The compression of ECG signal reduces the storage and transmission cost. The important factor to be considered in compression of ECG signal is to obtain maximum data reduction. The clinically important features of ECG signal must be preserved after reconstruction
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