Wavelet transform in electrocardiography--data compression.
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.
Provazník
I
I
Department of Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, Technical University Brno, Czech Republic. provazni@dbme.fee.vutbr.cz
Kozumplík
J
J
D000162:Acoustics; D000465:Algorithms; D004562:Electrocardiography; D005583:Fourier Analysis; D006801:Humans; D010363:Pattern Recognition, Automated; D012146:Rest / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D013685:Telecommunications; D013689:Telephone; D013997:Time Factors