{"title":"从心电图和其他相关信号定位心跳","authors":"Dan Li, S. Bass, S. Hurley","doi":"10.1109/ICCIA.2018.00032","DOIUrl":null,"url":null,"abstract":"The electrocardiogram (ECG) is the main source of heartbeat analysis. However, analyzing the ECG alone can be problematic because ECG data can be noisy. This research analyzes the associations between ECG and a variety of biomedical signals, and uses these associations to detect heartbeat locations with a higher accuracy than just analyzing ECG alone.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Locating Heartbeats from Electrocardiograms and Other Correlated Signals\",\"authors\":\"Dan Li, S. Bass, S. Hurley\",\"doi\":\"10.1109/ICCIA.2018.00032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The electrocardiogram (ECG) is the main source of heartbeat analysis. However, analyzing the ECG alone can be problematic because ECG data can be noisy. This research analyzes the associations between ECG and a variety of biomedical signals, and uses these associations to detect heartbeat locations with a higher accuracy than just analyzing ECG alone.\",\"PeriodicalId\":297098,\"journal\":{\"name\":\"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIA.2018.00032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIA.2018.00032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Locating Heartbeats from Electrocardiograms and Other Correlated Signals
The electrocardiogram (ECG) is the main source of heartbeat analysis. However, analyzing the ECG alone can be problematic because ECG data can be noisy. This research analyzes the associations between ECG and a variety of biomedical signals, and uses these associations to detect heartbeat locations with a higher accuracy than just analyzing ECG alone.