{"title":"驾驶电动轮椅时的短期心率变异性分析","authors":"N. Bu, H. Ohtsuka","doi":"10.1109/ICIIBMS46890.2019.8991482","DOIUrl":null,"url":null,"abstract":"Heart rate variability (HRV) is an important biomarker for monitoring physical and mental conditions of human beings when they are executing a task. This study attempts to achieve HRV analysis to investigate variation of user’s stress level during driving a powered wheelchair. In such cases, situations and environment issues during driving are temporary and always change dynamically. This means most of the traditional HRV analysis methods are not appropriate, since there is a requirement of relatively long HRV data for each evaluation, for example five minutes. In order to deal with this problem, this paper applies four short-term HRV analysis indices to evaluate user’s stress level during driving and compares evaluation performance of these indices. Wheelchair driving experiments have been conducted with two test courses, namely, a straight course and a crank course. Since the time durations of driving through these courses were relatively short, the evaluation window length of HRV data was set as 15 and 20 s, respectively. With an overlap of 10 s, the evaluation has been achieved with time resolution as 5 and 10 s.","PeriodicalId":444797,"journal":{"name":"2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Short-term Heart Rate Variability Analysis during Driving a Powered Wheelchair\",\"authors\":\"N. Bu, H. Ohtsuka\",\"doi\":\"10.1109/ICIIBMS46890.2019.8991482\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Heart rate variability (HRV) is an important biomarker for monitoring physical and mental conditions of human beings when they are executing a task. This study attempts to achieve HRV analysis to investigate variation of user’s stress level during driving a powered wheelchair. In such cases, situations and environment issues during driving are temporary and always change dynamically. This means most of the traditional HRV analysis methods are not appropriate, since there is a requirement of relatively long HRV data for each evaluation, for example five minutes. In order to deal with this problem, this paper applies four short-term HRV analysis indices to evaluate user’s stress level during driving and compares evaluation performance of these indices. Wheelchair driving experiments have been conducted with two test courses, namely, a straight course and a crank course. Since the time durations of driving through these courses were relatively short, the evaluation window length of HRV data was set as 15 and 20 s, respectively. With an overlap of 10 s, the evaluation has been achieved with time resolution as 5 and 10 s.\",\"PeriodicalId\":444797,\"journal\":{\"name\":\"2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIIBMS46890.2019.8991482\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIIBMS46890.2019.8991482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Short-term Heart Rate Variability Analysis during Driving a Powered Wheelchair
Heart rate variability (HRV) is an important biomarker for monitoring physical and mental conditions of human beings when they are executing a task. This study attempts to achieve HRV analysis to investigate variation of user’s stress level during driving a powered wheelchair. In such cases, situations and environment issues during driving are temporary and always change dynamically. This means most of the traditional HRV analysis methods are not appropriate, since there is a requirement of relatively long HRV data for each evaluation, for example five minutes. In order to deal with this problem, this paper applies four short-term HRV analysis indices to evaluate user’s stress level during driving and compares evaluation performance of these indices. Wheelchair driving experiments have been conducted with two test courses, namely, a straight course and a crank course. Since the time durations of driving through these courses were relatively short, the evaluation window length of HRV data was set as 15 and 20 s, respectively. With an overlap of 10 s, the evaluation has been achieved with time resolution as 5 and 10 s.