{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T03:23:30Z","timestamp":1775273010195,"version":"3.50.1"},"reference-count":151,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T00:00:00Z","timestamp":1734480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Comput. Sci."],"abstract":"<jats:p>Over the last few years, wearable devices have witnessed immense changes in terms of sensing capabilities. Wearable devices, with their ever-increasing number of sensors, have been instrumental in monitoring human activities, health-related indicators, and overall wellness. One health-related area that has rapidly adopted wearable devices is the mental health monitoring and well-being area, which covers problems such as psychological distress. The continuous monitoring capability of wearable devices allows the detection and monitoring of stress, thus enabling early detection of mental health problems. In this paper, we present a systematic review of the different types of sensors and wearable devices used by researchers to detect and monitor stress in individuals. We identify and detail the tasks such as data collection, data pre-processing, features computation, and training of the model explored by such research works. We review each step involved in stress detection and monitoring. We also discuss the scope and opportunities for further research that deals with the management of stress once it is detected.<\/jats:p>","DOI":"10.3389\/fcomp.2024.1478851","type":"journal-article","created":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T06:44:18Z","timestamp":1734504258000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":41,"title":["Detection and monitoring of stress using wearables: a systematic review"],"prefix":"10.3389","volume":"6","author":[{"given":"Anuja","family":"Pinge","sequence":"first","affiliation":[]},{"given":"Vinaya","family":"Gad","sequence":"additional","affiliation":[]},{"given":"Dheryta","family":"Jaisighani","sequence":"additional","affiliation":[]},{"given":"Surjya","family":"Ghosh","sequence":"additional","affiliation":[]},{"given":"Sougata","family":"Sen","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2024,12,18]]},"reference":[{"key":"B1","unstructured":"Stress Monitor for Watch\n          \n          2023"},{"key":"B2","doi-asserted-by":"publisher","first-page":"101824","DOI":"10.1016\/j.artmed.2020.101824","article-title":"Wearable sensor-based evaluation of psychosocial stress in patients with metabolic syndrome","volume":"104","author":"Akbulut","year":"2020","journal-title":"Artif. 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