Empirical Wavelet Transform Based ECG Signal Compression

ABSTRACT

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.

Keywords:

• CR
• Empirical wavelets
• EWT
• Threshold factor

Additional information

Notes on contributors

Rakesh Kumar

Rakesh Kumar was born in Jammu, India, in 1990. He received his B. Tech degree in electronics and communications engineering from Govt. College of Engineering and Technology, Jammu, in 2011. Presently, he is pursuing M. Tech in electronics and communications engineering from National Institute of Technology Jalandhar. His research interests are in biomedical signal processing and image processing.

E-mail: [email protected]

Indu Saini

Indu Saini was born in Ferozepur, India, in 1971. She received her B. Tech degree in electronics and communication engineering from Guru Nanak Dev University, India, in 1994 and then obtained her M. Tech (by Research) and PhD degree in electronics and communication engineering from Dr B. R. Ambedkar National Institute of Technology Jalandhar, where she is also serving as assistant professor in Electronics & Communication Engineering Department since 2002. Her professional research interests are very large scale integration (VLSI) design, biomedical signal processing, and machine learning algorithms.

E-mail: [email protected]