Bozidara Cvetkovic, M. Gjoreski, Jure Sorn, Martin Freser, Maciej Bogdanski, Katarzyna Jackowska, Michal Kosiedowski, Aleksander Stroinski, M. Luštrek
{"title":"Management of Physical, Mental and Environmental Stress at the Workplace","authors":"Bozidara Cvetkovic, M. Gjoreski, Jure Sorn, Martin Freser, Maciej Bogdanski, Katarzyna Jackowska, Michal Kosiedowski, Aleksander Stroinski, M. Luštrek","doi":"10.1109/IE.2017.20","DOIUrl":null,"url":null,"abstract":"We present the Fit4Work system for monitoring and management of physical, mental and environmental stress at the workplace. The system was designed specifically for older workers who are subject to sedentary stressful work in an office environment. It uses commercially available devices and intelligent methods, which utilize machine-learning models to monitor the three aspects of the users' lifestyle, and provide recommendations for improving them. The results show that the system can adequately recognize the user's physical activities, estimate energy expenditure and detect mental stress, as well as recognize and reason about unhealthy environment. The system provides recommendations according to the monitoring results.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Intelligent Environments (IE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IE.2017.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
We present the Fit4Work system for monitoring and management of physical, mental and environmental stress at the workplace. The system was designed specifically for older workers who are subject to sedentary stressful work in an office environment. It uses commercially available devices and intelligent methods, which utilize machine-learning models to monitor the three aspects of the users' lifestyle, and provide recommendations for improving them. The results show that the system can adequately recognize the user's physical activities, estimate energy expenditure and detect mental stress, as well as recognize and reason about unhealthy environment. The system provides recommendations according to the monitoring results.