An electrocardiogram signal compression techniques: a comprehensive review
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Abstract
In spite of development in digital storage and communication technology, the demand for data compression is ever increasing. The ECG data requires about 40–50 MB per channel space for 24-h recording. Limitations of storage size, higher bandwidth and the extra transmission time to these signals over different communication channels force to study an efficient compression algorithm. The primary objective is to retain the most useful clinical information while compressing the ECG signals to an acceptable size. The literature proposes many algorithms to implement ECG compression. It is the observation that, among all, the wavelet-based algorithms provide better compression performance. This paper is a review of most promising algorithms of ECG compression with emphasis to wavelet-based ECG signal compression.
Keywords
Compression ratio ECG Entropy coding EZW Percentage root mean difference SPIHT Quantization Thresholding Wavelet transformReferences
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