Vector quantization and signal compression
Vector quantization and signal compression
IEEE Computational Science & Engineering
Guest Editorial Special Issue on Emerging Health Telematics Applications in Europe
IEEE Transactions on Information Technology in Biomedicine
Optimal zonal wavelet-based ECG data compression for a mobile telecardiology system
IEEE Transactions on Information Technology in Biomedicine
ECG data compression using wavelets and higher order statistics methods
IEEE Transactions on Information Technology in Biomedicine
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An algorithm of the ECG signal compression, based on the combination of the run length encoding and discrete wavelet transform, intended for a simulated transmission via the IEEE 802.11b WLAN channel, is presented in this work. The algorithm consists of two basic phases that are ECG signal compression and transmission via the IEEE 802.11b WLAN channel. The algorithm is based on applying the run length coding upon the thresholded discrete wavelet transform of the real ECG signal. In terms of compression efficiency, applying the compression procedure on several ECG data, presenting diverse cardiac status, selected from the MIT-BIH arrhythmia data base, achieves compression ratio of around 10:1, normalized root mean squared error (NRMSE) of 4% and (mean± standard deviation) of the difference between the restituted ECG signal and the original one of around (3 10-6) ± 0.03. The end point of this work is to simulate transmission of the compressed ECG signal via the IEEE 802.11b WLAN channel. The unavoidable distortion introduced by the transmission channel reduces the compression ratio to about 6.7:1 in the cost of preserving the ECG signal fidelity.