{"title":"基于鲁棒回归的心电信号自适应感知R-R区间预测","authors":"M. Momot, A. Momot, E. Piekar","doi":"10.1109/SPS.2015.7168280","DOIUrl":null,"url":null,"abstract":"The paper presents the concept of selective transmission of the ECG signal between the recorder located on the body of the monitored person and the mobile device. This concept is based on the possibility of energy saving by transmitting only necessary parts of signal. For the ECG, the most important data consist of waves P-QRS-T waves, located only in a neighborhood of the central point on timeline. This suggests methods of predicting the position of the center points of subsequent cardiac cycles in order to select fragments to be transmitted. The paper proposes use of the regression function to determine the positions of these points on the basis of a finite number of values recorded in recent history. The parameters of the regression function are selected using an algorithm of robust estimation.","PeriodicalId":193902,"journal":{"name":"2015 Signal Processing Symposium (SPSympo)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"R-R interval prediction for adaptive sensing of ECG signal using robust regression\",\"authors\":\"M. Momot, A. Momot, E. Piekar\",\"doi\":\"10.1109/SPS.2015.7168280\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents the concept of selective transmission of the ECG signal between the recorder located on the body of the monitored person and the mobile device. This concept is based on the possibility of energy saving by transmitting only necessary parts of signal. For the ECG, the most important data consist of waves P-QRS-T waves, located only in a neighborhood of the central point on timeline. This suggests methods of predicting the position of the center points of subsequent cardiac cycles in order to select fragments to be transmitted. The paper proposes use of the regression function to determine the positions of these points on the basis of a finite number of values recorded in recent history. The parameters of the regression function are selected using an algorithm of robust estimation.\",\"PeriodicalId\":193902,\"journal\":{\"name\":\"2015 Signal Processing Symposium (SPSympo)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Signal Processing Symposium (SPSympo)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPS.2015.7168280\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing Symposium (SPSympo)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPS.2015.7168280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
R-R interval prediction for adaptive sensing of ECG signal using robust regression
The paper presents the concept of selective transmission of the ECG signal between the recorder located on the body of the monitored person and the mobile device. This concept is based on the possibility of energy saving by transmitting only necessary parts of signal. For the ECG, the most important data consist of waves P-QRS-T waves, located only in a neighborhood of the central point on timeline. This suggests methods of predicting the position of the center points of subsequent cardiac cycles in order to select fragments to be transmitted. The paper proposes use of the regression function to determine the positions of these points on the basis of a finite number of values recorded in recent history. The parameters of the regression function are selected using an algorithm of robust estimation.