Title :
Quantification of real-time ECG data compression algorithms
Author :
Banville, I. ; Armstrong, S.
Author_Institution :
Dept. of Biomed. Eng., Alabama Univ., Birmingham, AL, USA
Abstract :
We simulated five real-time data compression algorithms on cardiac electrograms to determine which would maximize the efficiency of memory usage in medical devices: Zero Order Prediction tolerance comparison (ZOP), First Order Prediction tolerance comparison (FOP), Differential Pulse Code Modulation (DPCM), the Fan, and Second Differences (SD). The Fan and FOP methods ranked first and second for the quality of the compressed waveform. The predicted storage rates for waveforms sampled at 200 Hz with the Fan and FOP were 75 and 95 bytes/s, respectively with compression ratios of 6:1 and 5:1, respectively
Keywords :
data compression; differential pulse code modulation; electrocardiography; medical signal processing; real-time systems; 200 Hz; 75 byte/s; 95 byte/s; Differential Pulse Code Modulation; ECG; Fan; First Order Prediction tolerance comparison; Second Differences; Zero Order Prediction tolerance comparison; cardiac electrogram; medical device; real-time data compression algorithm; Compression algorithms; Data compression; Electrocardiography; Modulation coding; Predictive models; Pulse compression methods; Pulse measurements; Pulse modulation; Redundancy; Sampling methods;
Conference_Titel :
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.802331
