Ye Wang, Xuezhi Yang, Xuenan Liu, Rencheng Song, J Zhang
{"title":"用非接触方法远程评估生理参数检测精神压力","authors":"Ye Wang, Xuezhi Yang, Xuenan Liu, Rencheng Song, J Zhang","doi":"10.1117/12.2682510","DOIUrl":null,"url":null,"abstract":"In this study, we present a new method for remote detection of mental stress via webcam. The system is based on remote Photoplethysmograph (rPPG) obtained from face video frames of heart rate, breathing rate, and pulse rate variability (PRV). The experiment collected pulse wave data from 14 healthy students with a stress distribution consisting of four phases: Rest, Stroop-Color-Word Test, Mental Arithmetic Task, and Recovery. We combined the stress questionnaire to select data to assess the human autonomic response to stress and recovery, the results showed significant differences in frequency domain characteristics and nonlinear parameters between phases. The average classification accuracy under different stress sources was 80.31%. The results demonstrate the applicability and convenience of the remote stress detection method. It can be used without disturbing a person’s daily life and provides an alternative to traditional contact techniques for those who want to monitor stress levels regularly.","PeriodicalId":440430,"journal":{"name":"International Conference on Electronic Technology and Information Science","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Remote assessment of physiological parameters by non-contact methods to detect mental stress\",\"authors\":\"Ye Wang, Xuezhi Yang, Xuenan Liu, Rencheng Song, J Zhang\",\"doi\":\"10.1117/12.2682510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, we present a new method for remote detection of mental stress via webcam. The system is based on remote Photoplethysmograph (rPPG) obtained from face video frames of heart rate, breathing rate, and pulse rate variability (PRV). The experiment collected pulse wave data from 14 healthy students with a stress distribution consisting of four phases: Rest, Stroop-Color-Word Test, Mental Arithmetic Task, and Recovery. We combined the stress questionnaire to select data to assess the human autonomic response to stress and recovery, the results showed significant differences in frequency domain characteristics and nonlinear parameters between phases. The average classification accuracy under different stress sources was 80.31%. The results demonstrate the applicability and convenience of the remote stress detection method. It can be used without disturbing a person’s daily life and provides an alternative to traditional contact techniques for those who want to monitor stress levels regularly.\",\"PeriodicalId\":440430,\"journal\":{\"name\":\"International Conference on Electronic Technology and Information Science\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Electronic Technology and Information Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2682510\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Electronic Technology and Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2682510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Remote assessment of physiological parameters by non-contact methods to detect mental stress
In this study, we present a new method for remote detection of mental stress via webcam. The system is based on remote Photoplethysmograph (rPPG) obtained from face video frames of heart rate, breathing rate, and pulse rate variability (PRV). The experiment collected pulse wave data from 14 healthy students with a stress distribution consisting of four phases: Rest, Stroop-Color-Word Test, Mental Arithmetic Task, and Recovery. We combined the stress questionnaire to select data to assess the human autonomic response to stress and recovery, the results showed significant differences in frequency domain characteristics and nonlinear parameters between phases. The average classification accuracy under different stress sources was 80.31%. The results demonstrate the applicability and convenience of the remote stress detection method. It can be used without disturbing a person’s daily life and provides an alternative to traditional contact techniques for those who want to monitor stress levels regularly.