Wavelet and wavelet packet compression of electrocardiograms

• Published in: IEEE transactions on biomedical engineering Vol. 44; no. 5; pp. 394 - 402
• Main Author: Hilton, M.L.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.1997; Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Biological and medical sciences; Cardiology; Compression algorithms; Data compression; Electrocardiography; Electrocardiography, Ambulatory; Electrocardiography. Vectocardiography; Electrodiagnosis. Electric activity recording; Filters; Humans; Investigative techniques, diagnostic techniques (general aspects); Medical sciences; Pilot Projects; Signal analysis; Signal Processing, Computer-Assisted; Tachycardia, Supraventricular - diagnosis; Tachycardia, Ventricular - diagnosis; Wavelet analysis; Wavelet packets; Wavelet transforms; Holter recording; Human; Experimental data; Electrical activity; Data compression; Electrodiagnosis; Algorithm performance; Wavelet transformation; Coding; Electrocardiography; Myocardium; Signal processing; Circulatory system; Diagnosis; Technique; Comparative study
• ISSN: 0018-9294
• DOI: 10.1109/10.568915

Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data. Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECG's are clinically useful.