{"title":"使用IR-UWB雷达传感器分析睡眠期间的运动","authors":"Jae Min Lee, J. Choi, S. Cho","doi":"10.1109/ICNIDC.2016.7974622","DOIUrl":null,"url":null,"abstract":"An IR-UWB radar sensor could be used to monitor vital signs such as breathing, heartbeat rate, and movement during sleep with non-contact method. In most sleep monitoring system, heartbeat rate and respiration are mostly analyzed. In this paper, we propose an algorithm for analyzing the human body movements during sleep using an IR-UWB radar sensor. To catch the detail movements, we minimized the transition time for calculating a movement index. The movements are categorized as four kinds based on the moving part of body. The four parts are arms, legs, head, and body. Each part is also divided as three grades based on the moving degree. To prove the performance of our algorithm, we tested in real-world during 1 night. The test result proved utility of the proposed algorithm.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Movement analysis during sleep using an IR-UWB radar sensor\",\"authors\":\"Jae Min Lee, J. Choi, S. Cho\",\"doi\":\"10.1109/ICNIDC.2016.7974622\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An IR-UWB radar sensor could be used to monitor vital signs such as breathing, heartbeat rate, and movement during sleep with non-contact method. In most sleep monitoring system, heartbeat rate and respiration are mostly analyzed. In this paper, we propose an algorithm for analyzing the human body movements during sleep using an IR-UWB radar sensor. To catch the detail movements, we minimized the transition time for calculating a movement index. The movements are categorized as four kinds based on the moving part of body. The four parts are arms, legs, head, and body. Each part is also divided as three grades based on the moving degree. To prove the performance of our algorithm, we tested in real-world during 1 night. The test result proved utility of the proposed algorithm.\",\"PeriodicalId\":439987,\"journal\":{\"name\":\"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNIDC.2016.7974622\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNIDC.2016.7974622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Movement analysis during sleep using an IR-UWB radar sensor
An IR-UWB radar sensor could be used to monitor vital signs such as breathing, heartbeat rate, and movement during sleep with non-contact method. In most sleep monitoring system, heartbeat rate and respiration are mostly analyzed. In this paper, we propose an algorithm for analyzing the human body movements during sleep using an IR-UWB radar sensor. To catch the detail movements, we minimized the transition time for calculating a movement index. The movements are categorized as four kinds based on the moving part of body. The four parts are arms, legs, head, and body. Each part is also divided as three grades based on the moving degree. To prove the performance of our algorithm, we tested in real-world during 1 night. The test result proved utility of the proposed algorithm.