{"title":"基于生物雷达的远程心理工作量估算","authors":"L. Anishchenko","doi":"10.23919/EMF-MED.2018.8526052","DOIUrl":null,"url":null,"abstract":"this work presents a new unobtrusive technique for remote mental workload estimation by a bioradar. The study explores the relationship between mental workload and variation of respiration and heartbeat patterns. The experiments were conducted in laboratory conditions. During the experiments, volunteers were asked to perform a mental arithmetic task. The information about variation of vital signs registered by a bioradar was used to detect the presence of mental workload. We achieved an accuracy of 0.87 and Cohen's kappa of 0.75 in the calm state/mental workload classification.","PeriodicalId":134768,"journal":{"name":"2018 EMF-Med 1st World Conference on Biomedical Applications of Electromagnetic Fields (EMF-Med)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Remote Mental Workload Estimation by a Bioradar\",\"authors\":\"L. Anishchenko\",\"doi\":\"10.23919/EMF-MED.2018.8526052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"this work presents a new unobtrusive technique for remote mental workload estimation by a bioradar. The study explores the relationship between mental workload and variation of respiration and heartbeat patterns. The experiments were conducted in laboratory conditions. During the experiments, volunteers were asked to perform a mental arithmetic task. The information about variation of vital signs registered by a bioradar was used to detect the presence of mental workload. We achieved an accuracy of 0.87 and Cohen's kappa of 0.75 in the calm state/mental workload classification.\",\"PeriodicalId\":134768,\"journal\":{\"name\":\"2018 EMF-Med 1st World Conference on Biomedical Applications of Electromagnetic Fields (EMF-Med)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 EMF-Med 1st World Conference on Biomedical Applications of Electromagnetic Fields (EMF-Med)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/EMF-MED.2018.8526052\",\"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 EMF-Med 1st World Conference on Biomedical Applications of Electromagnetic Fields (EMF-Med)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/EMF-MED.2018.8526052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
this work presents a new unobtrusive technique for remote mental workload estimation by a bioradar. The study explores the relationship between mental workload and variation of respiration and heartbeat patterns. The experiments were conducted in laboratory conditions. During the experiments, volunteers were asked to perform a mental arithmetic task. The information about variation of vital signs registered by a bioradar was used to detect the presence of mental workload. We achieved an accuracy of 0.87 and Cohen's kappa of 0.75 in the calm state/mental workload classification.