Compression of ECG Signals Using a Novel Discrete Wavelet Transform Algorithm for Dynamic Arrythmia Database
ECG signals play an important role in the primary diagnosis, prognosis and survival analysis of heart diseases. In this paper, a new approach based on the threshold value of ECG signal determination is proposed using Wavelet Transform coefficients. The electrocardiogram signal contains an important amount of information that can be exploited in different manners . Different ECG signals are used to verify the proposed method. A wavelet-based electrocardiogram (ECG) data compression algorithm for dynamic Arrythmia database is presented. The ECG signal is first processed then discrete wavelet is sent to the preprocessed signal. Compression is achieved by variable length based on run length encoding to compress significance and direct binary representation for representing significant coefficients. The proposed algorithm is compared with direct wavelet based compression algorithm represents superior performance.
KeywordsArrythmia Orientation tree Denoising factor Biorthogonal wavelets Holter records
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