{"title":"Mobile real-time arousal detection","authors":"V. Alexandratos, M. Bulut, R. Jasinschi","doi":"10.1109/ICASSP.2014.6854432","DOIUrl":null,"url":null,"abstract":"We introduce a mobile system that is able to detect arousal in realtime based on electrocardiogram and electrodermal activity. The system is using an Android smartphone and wearable sensors, which include a smart watch and a heart rate belt that gather skin conductance and heart rate data, respectively. Algorithms for processing the skin conductance and heart rate data, as well as an automated method for labeling the collected `arousal' and `non-arousal' experimental data are developed. Small-scale user tests show 84% 10-fold, 83% between-subject, and 68% new-subject arousal detection accuracy.","PeriodicalId":6545,"journal":{"name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"174 1","pages":"4394-4398"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2014.6854432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
We introduce a mobile system that is able to detect arousal in realtime based on electrocardiogram and electrodermal activity. The system is using an Android smartphone and wearable sensors, which include a smart watch and a heart rate belt that gather skin conductance and heart rate data, respectively. Algorithms for processing the skin conductance and heart rate data, as well as an automated method for labeling the collected `arousal' and `non-arousal' experimental data are developed. Small-scale user tests show 84% 10-fold, 83% between-subject, and 68% new-subject arousal detection accuracy.