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An algorithm combining empirical and discrete wavelet transforms provides efficient ECG signal compression with high compression ratios and low distortion, which may be useful for telemedicine applications.
Transmission of biomedical signals over telephone lines or other communication channels is currently an important issue for the telemedicine applications. An efficient compression algorithm is needed to achieve a reduced information rate, for the storage and transmission purposes. In this paper, empirical wavelet transform (EWT) along with discrete wavelet transform (DWT) has been used for compression and reconstruction of the ECG signals. Key point lies in using different threshold for different modes obtained by applying EWT. Proposed algorithm has been tested on self-acquired (on BIOPAC®MP150) ECG signals of 20 subjects, each of 12 minutes duration and 360,000 samples with sampling rate 500 Hz and average 31.2 compression ratio (CR) and 3.28% percentage ratio distortion (PRD) have been obtained. Algorithm has also been applied on all 48 arrhythmia signals of Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH)77777\+766 database, each of 30 minutes duration and 650,000 samples, sampled at 360 Hz and an average 33.1 CR and 3.3% PRD are obtained.
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Kumar et al. (2014) studied this question.
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