Using contexts and R–R interval estimation in lossless ECG compression

• Published in: Computer methods and programs in biomedicine Vol. 67; no. 3; pp. 177 - 186
• Main Authors: GIURCANEANU, Ciprian Doru, TABUS, Ioan, MEREUTA, Serban
• Format: Journal Article
• Language: English
• Published: Shannon Elsevier Ireland Ltd 01.03.2002; Elsevier Science
• Subjects: Algorithms; Biological and medical sciences; Computerized, statistical medical data processing and models in biomedicine; Context coding; Electrocardiography - methods; Electrocardiography. Vectocardiography; Electrodiagnosis. Electric activity recording; Escape codes; General aspects. Methods; Heart - physiopathology; Humans; Investigative techniques, diagnostic techniques (general aspects); Lossless coding; Medical sciences; R–R interval; R–R interval; Context coding; Escape codes; Lossless coding; Context; Human; Evaluation; Parameter estimation; Data compression; QRS interval; Experimental study; Algorithm; RR interval; Electrodiagnosis; Biomedical data processing; Coding; Electrocardiography; Signal processing; Detection; Biomedical engineering
• ISSN: 0169-2607; 1872-7565
• DOI: 10.1016/S0169-2607(01)00126-2

The paper presents a new lossless ECG compression scheme. The short-term predictor and the coder use conditioning on a small number of contexts. The long-term prediction is based on an algorithm for R–R interval estimation. Several QRS detection algorithms are investigated to select a low complexity and reliable detection algorithm. The coding of prediction residuals uses primarily the Golomb-Rice (GR) codes, but, to improve the coding results, escape codes GR–ESC are used in some contexts for a limited number of samples. Experimental results indicate the good overall performance of the lossless ECG compression algorithms (reducing the storage needs from 12 to about 3–4 bits per sample). The scheme consistently outperforms other waveform or general purpose coding algorithms.