Wavelet transform in electrocardiography--data compression
Language English Country Ireland Media print
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
9291025
DOI
10.1016/s1386-5056(97)00040-3
PII: S1386-5056(97)00040-3
Knihovny.cz E-resources
- MeSH
- Acoustics MeSH
- Algorithms MeSH
- Time Factors MeSH
- Electrocardiography * MeSH
- Fourier Analysis MeSH
- Humans MeSH
- Rest physiology MeSH
- Signal Processing, Computer-Assisted * MeSH
- Pattern Recognition, Automated MeSH
- Telephone MeSH
- Telecommunications MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
An application of the wavelet transform to electrocardiography is described in the paper. The transform is used as a first stage of a lossy compression algorithm for efficient coding of rest ECG signals. The proposed technique is based on the decomposition of the ECG signal into a set of basic functions covering the time-frequency domain. Thus, non-stationary character of ECG data is considered. Some of the time-frequency signal components are removed because of their low influence to signal characteristics. Resulting components are efficiently coded by quantization, composition into a sequence of coefficients and compression by a run-length coder and a entropic Huffman coder. The proposed wavelet-based compression algorithm can compress data to average code length about 1 bit/sample. The algorithm can be also implemented to a real-time processing system when wavelet transform is computed by fast linear filters described in the paper.
References provided by Crossref.org
A Comparative Analysis of Methods for Evaluation of ECG Signal Quality after Compression
