{"title":"Efficient electrocardiogram (ECG) lossy compression scheme","authors":"A. Hatim, R. Latif, Oussama El Bachari, M. Arioua","doi":"10.1109/ICMCS.2016.7905608","DOIUrl":null,"url":null,"abstract":"A new electrocardiogram (ECG) lossy compression scheme has been developed. The algorithm can reach high compression ratios with a reduced error which makes it suitable for real-time electrocardiogram monitoring. The new algorithm is based on delta coding technique. Low and high coding categories were made to encode the differences and insure an optimized compressed signal. In addition the number of successive coded differences is flexible and defined with a window size. A new frame format was developed to transmit data. The algorithm has been verified using multiple and most frequent normal and pathological types of cardiac signals from MIT-BIH physionet data bases. The algorithm can reach a mean compression ratio of 33.45 and a mean PRD of 0.25%. The proposed algorithm has a low complexity and is very suitable for hardware designs.","PeriodicalId":345854,"journal":{"name":"2016 5th International Conference on Multimedia Computing and Systems (ICMCS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 5th International Conference on Multimedia Computing and Systems (ICMCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMCS.2016.7905608","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A new electrocardiogram (ECG) lossy compression scheme has been developed. The algorithm can reach high compression ratios with a reduced error which makes it suitable for real-time electrocardiogram monitoring. The new algorithm is based on delta coding technique. Low and high coding categories were made to encode the differences and insure an optimized compressed signal. In addition the number of successive coded differences is flexible and defined with a window size. A new frame format was developed to transmit data. The algorithm has been verified using multiple and most frequent normal and pathological types of cardiac signals from MIT-BIH physionet data bases. The algorithm can reach a mean compression ratio of 33.45 and a mean PRD of 0.25%. The proposed algorithm has a low complexity and is very suitable for hardware designs.