Complex study on compression of ECG signals using novel single-cycle fractal-based algorithm and SPIHT
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Compression of ECG signal is essential especially in the area of signal transmission in telemedicine. There exist many compression algorithms which are described in various details, tested on various datasets and their performance is expressed by different ways. There is a lack of standardization in this area. This study points out these drawbacks and presents new compression algorithm which is properly described, tested and objectively compared with other authors. This study serves as an example how the standardization should look like. Single-cycle fractal-based (SCyF) compression algorithm is introduced and tested on 4 different databases-CSE database, MIT-BIH arrhythmia database, High-frequency signal and Brno University of Technology ECG quality database (BUT QDB). SCyF algorithm is always compared with well-known algorithm based on wavelet transform and set partitioning in hierarchical trees in terms of efficiency (2 methods) and quality/distortion of the signal after compression (12 methods). Detail analysis of the results is provided. The results of SCyF compression algorithm reach up to avL=0.4460 bps and PRDN=2.8236%.
Keywordscompression, ECG, electrocardiogram, CSE database, MIT-BIH arrhythmia database, SPIHT, fractals
Document typePeer reviewed
Document versionFinal PDF
SourceScientific Reports. 2020, vol. 10, issue 1, p. 1-15.