Mahbubur Rahman, Rummana Bari, Amin Ahsan Ali, Moushumi Sharmin, Andrew Raij, Karen Hovsepian, Syed Monowar Hossain, Emre Ertin, Ashley Kennedy, David H Epstein, Kenzie L Preston, Michelle Jobes, J Gayle Beck, Satish Kedia, Kenneth D Ward, Mustafa al'Absi, Santosh Kumar
{"title":"Are We There Yet? Feasibility of Continuous Stress Assessment via Wireless Physiological Sensors.","authors":"Mahbubur Rahman, Rummana Bari, Amin Ahsan Ali, Moushumi Sharmin, Andrew Raij, Karen Hovsepian, Syed Monowar Hossain, Emre Ertin, Ashley Kennedy, David H Epstein, Kenzie L Preston, Michelle Jobes, J Gayle Beck, Satish Kedia, Kenneth D Ward, Mustafa al'Absi, Santosh Kumar","doi":"10.1145/2649387.2649433","DOIUrl":null,"url":null,"abstract":"<p><p>Stress can lead to headaches and fatigue, precipitate addictive behaviors (e.g., smoking, alcohol and drug use), and lead to cardiovascular diseases and cancer. Continuous assessment of stress from sensors can be used for timely delivery of a variety of interventions to reduce or avoid stress. We investigate the feasibility of continuous stress measurement via two field studies using wireless physiological sensors - a four-week study with illicit drug users (<i>n</i> = 40), and a one-week study with daily smokers and social drinkers (<i>n</i> = 30). We find that 11+ hours/day of usable data can be obtained in a 4-week study. Significant learning effect is observed after the first week and data yield is seen to be increasing over time even in the fourth week. We propose a framework to analyze sensor data yield and find that losses in wireless channel is negligible; the main hurdle in further improving data yield is the attachment constraint. We show the feasibility of measuring stress minutes preceding events of interest and observe the sensor-derived stress to be rising prior to self-reported stress and smoking events.</p>","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4374173/pdf/nihms-671146.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2649387.2649433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Stress can lead to headaches and fatigue, precipitate addictive behaviors (e.g., smoking, alcohol and drug use), and lead to cardiovascular diseases and cancer. Continuous assessment of stress from sensors can be used for timely delivery of a variety of interventions to reduce or avoid stress. We investigate the feasibility of continuous stress measurement via two field studies using wireless physiological sensors - a four-week study with illicit drug users (n = 40), and a one-week study with daily smokers and social drinkers (n = 30). We find that 11+ hours/day of usable data can be obtained in a 4-week study. Significant learning effect is observed after the first week and data yield is seen to be increasing over time even in the fourth week. We propose a framework to analyze sensor data yield and find that losses in wireless channel is negligible; the main hurdle in further improving data yield is the attachment constraint. We show the feasibility of measuring stress minutes preceding events of interest and observe the sensor-derived stress to be rising prior to self-reported stress and smoking events.