{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T02:45:50Z","timestamp":1761965150268,"version":"3.40.5"},"reference-count":27,"publisher":"IGI Global","issue":"3","license":[{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7,1]]},"abstract":"<p>In the software industry, where the quality of the output is based on human performance, fatigue can be a reason for performance degradation. Fatigue not only degrades quality, but is also a health risk factor. Sleep disorders, depression, and stress are all results of fatigue which can contribute to fatal problems. This article presents a comparative study of different techniques which can be used for detecting fatigue of programmers and data miners who spent lots of time in front of a computer screen. Machine learning can used for worker fatigue detection also, but there are some factors which are specific for software workers. One of such factors is screen illumination. Screen illumination is the light of the computer screen or laptop screen that is casted on the workers face and makes it difficult for the machine learning algorithm to extract the facial features. This article presents a comparative study of the techniques which can be used for general fatigue detection and identifies the best techniques.<\/p>","DOI":"10.4018\/ijehmc.2020070101","type":"journal-article","created":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T17:30:13Z","timestamp":1584725413000},"page":"1-8","source":"Crossref","is-referenced-by-count":28,"title":["A Survey on Fatigue Detection of Workers Using Machine Learning"],"prefix":"10.4018","volume":"11","author":[{"given":"Nisha","family":"Yadav","sequence":"first","affiliation":[{"name":"JSS Academy of Technical Education, Noida, India"}]},{"given":"Kakoli","family":"Banerjee","sequence":"additional","affiliation":[{"name":"JSS Academy of Technical Education, Noida, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2809-8455","authenticated-orcid":true,"given":"Vikram","family":"Bali","sequence":"additional","affiliation":[{"name":"JSS Academy of Technical Education, Noida, India"}]}],"member":"2432","reference":[{"issue":"2","key":"IJEHMC.2020070101-0","first-page":"3080","article-title":"Detection of drowsiness in human eye using SVM.","volume":"2","author":"C. J.Bharathi","year":"2014","journal-title":"International Journal of Innovative Research in Computer and Communication Engineering"},{"key":"IJEHMC.2020070101-1","unstructured":"CCOH. (n.d.). Fatigue [infographic]. Retrieved from https:\/\/www.ccohs.ca\/images\/products\/infographics\/download\/fatigue.jpg"},{"issue":"16","key":"IJEHMC.2020070101-2","first-page":"503","article-title":"Fatigue Detection Techniques: A Review.","volume":"117","author":"R.E.Chellappa","year":"2017","journal-title":"International Journal of Pure and Applied Mathematics"},{"key":"IJEHMC.2020070101-3","doi-asserted-by":"crossref","unstructured":"Chowdhury, R.S., & Kavakli, M.H. (2018). Sensor Applications and Physiological Features in Drivers\u2019 Drowsiness Detection: A Review. International Research Training Program.","DOI":"10.1109\/JSEN.2018.2807245"},{"key":"IJEHMC.2020070101-4","unstructured":"Dange, T. Y. (2013). Eye Estimation to detect Drowsiness. Proceedings of theNational Conference on Innovative Paradigms in Engineering and technology. Academic Press."},{"issue":"3","key":"IJEHMC.2020070101-5","first-page":"4469","article-title":"Analyzing the Biosignal to Make Fatigue Measurement as a Parameter for Mood Detection.","volume":"3","author":"C. H.Hajare","year":"2012","journal-title":"International Journal of Computer Science & Information and Technology"},{"key":"IJEHMC.2020070101-6","unstructured":"Hajare, S. D. (2011). A Survey on Mood Condition Detection and Fatigue Measurement Methodology. Proceedings of the2nd National Conference on Information and Communication Technology (pp. 11-13). Academic Press."},{"key":"IJEHMC.2020070101-7","unstructured":"Interdynamics. (2015). Risk based approach to managing fatigue. Retrieved from https:\/\/www.interdynamics.com\/wpcontent\/uploads\/2015\/07\/RiskBasedApproachToManagingFatigue.png"},{"key":"IJEHMC.2020070101-8","doi-asserted-by":"publisher","DOI":"10.1109\/ICECDS.2017.8390082"},{"issue":"5","key":"IJEHMC.2020070101-9","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1109\/TSMCA.2005.855922","article-title":"A probabilistic framework for modeling and real-time monitoring human fatigue.","volume":"36","author":"Q.Ji","year":"2006","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics. Part A, Systems and Humans"},{"key":"IJEHMC.2020070101-10","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2004.830974"},{"key":"IJEHMC.2020070101-11","doi-asserted-by":"publisher","DOI":"10.1109\/ICE.2018.8436252"},{"issue":"5","key":"IJEHMC.2020070101-12","first-page":"689","article-title":"Drowsiness detection system using Matlab.","volume":"6","author":"V. S.Kashyap","year":"2017","journal-title":"International Journal of Advance Research in Science and Engineering"},{"key":"IJEHMC.2020070101-13","first-page":"III","article-title":"Eye detection using color cues and projection functions.","volume":"3","author":"R. T.Kumar","year":"2002","journal-title":"Proceedings - International Conference on Image Processing"},{"key":"IJEHMC.2020070101-14","doi-asserted-by":"publisher","DOI":"10.1109\/PRIMEASIA.2010.5604919"},{"key":"IJEHMC.2020070101-15","doi-asserted-by":"publisher","DOI":"10.1109\/innovations.2016.7880030"},{"key":"IJEHMC.2020070101-16","doi-asserted-by":"publisher","DOI":"10.1109\/icta.2017.8336048"},{"key":"IJEHMC.2020070101-17","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2013.6557978"},{"key":"IJEHMC.2020070101-18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2816044"},{"key":"IJEHMC.2020070101-19","doi-asserted-by":"publisher","DOI":"10.1109\/cgiv.2016.33"},{"key":"IJEHMC.2020070101-20","doi-asserted-by":"publisher","DOI":"10.1109\/CASP.2016.7746183"},{"issue":"7","key":"IJEHMC.2020070101-21","first-page":"1","article-title":"Efficient Driver Fatigue Detection and Alerting System.","volume":"5","author":"M.Sontakke","year":"2015","journal-title":"International Journal of Scientific Research Publications"},{"key":"IJEHMC.2020070101-22","doi-asserted-by":"publisher","DOI":"10.1109\/RSETE.2011.5964969"},{"key":"IJEHMC.2020070101-23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2812208"},{"key":"IJEHMC.2020070101-24","doi-asserted-by":"publisher","DOI":"10.1109\/AFGR.1996.557289"},{"key":"IJEHMC.2020070101-25","doi-asserted-by":"publisher","DOI":"10.1109\/CMVIT.2017.25"},{"key":"IJEHMC.2020070101-26","doi-asserted-by":"publisher","DOI":"10.1109\/BMEI.2011.6098343"}],"container-title":["International Journal of E-Health and Medical Communications"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=251853","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T22:09:14Z","timestamp":1651874954000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJEHMC.2020070101"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2020,7,1]]},"references-count":27,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,7]]}},"URL":"https:\/\/doi.org\/10.4018\/ijehmc.2020070101","relation":{},"ISSN":["1947-315X","1947-3168"],"issn-type":[{"type":"print","value":"1947-315X"},{"type":"electronic","value":"1947-3168"}],"subject":[],"published":{"date-parts":[[2020,7,1]]}}}