A novel algorithm for wavelet based ECG signal coding

Wavelets have emerged as powerful tools for signal coding especially bio-signal processing. Wavelet transform is used to represent the signal to some other time–frequency representation better suited for detecting and removing redundancies. A novel algorithm for wavelet based ECG signal coding is proposed in this paper. Experimental results show that this algorithm outperforms than other coders such as Djohn, EZW, SPIHT, etc., exits in the literature in terms of simplicity and coding efficiency by successive partition the wavelet coefficients in the space frequency domain and send them using adaptive decimal to binary conversion. Proposed algorithm is significantly more efficient in compression, simple in implementation and in computation than the previously proposed coders. This algorithm is tested for 26 different records from MIT–BIH arrhythmia database and obtained an average percent root mean square difference as around 0.01–4.8% for an average compression ratio of 2:1 to 35:1. A compression ratio of 8.5108:1 is achieved for MIT–BIH arrhythmia database record 117 with a percent mean square difference as 1.29%.