{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T03:15:47Z","timestamp":1773890147965,"version":"3.50.1"},"reference-count":82,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T00:00:00Z","timestamp":1676505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001313","name":"Coventry University","doi-asserted-by":"publisher","award":["BDN68KDUX"],"award-info":[{"award-number":["BDN68KDUX"]}],"id":[{"id":"10.13039\/501100001313","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The concept of vehicle automation ceases to seem futuristic with the current advancement of the automotive industry. With the introduction of conditional automated vehicles, drivers are no longer expected to focus only on driving activities but are still required to stay alert to resume control. However, fluctuations in driving demands are known to alter the driver\u2019s mental workload (MWL), which might affect the driver\u2019s vehicle take-over capabilities. Driver mental workload can be specified as the driver\u2019s capacity for information processing for task performance. This paper summarizes the literature that relates to analysing driver mental workload through various in-vehicle physiological sensors focusing on cardiovascular and respiratory measures. The review highlights the type of study, hardware, method of analysis, test variable, and results of studies that have used physiological indices for MWL analysis in the automotive context.<\/jats:p>","DOI":"10.3390\/s23042214","type":"journal-article","created":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T02:04:03Z","timestamp":1676513043000},"page":"2214","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload Monitoring"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2328-0979","authenticated-orcid":false,"given":"Ashwini Kanakapura","family":"Sriranga","sequence":"first","affiliation":[{"name":"Institute for Clean Growth and Future Mobility, Coventry University, Coventry CV1 5FB, UK"}]},{"given":"Qian","family":"Lu","sequence":"additional","affiliation":[{"name":"Institute for Clean Growth and Future Mobility, Coventry University, Coventry CV1 5FB, UK"}]},{"given":"Stewart","family":"Birrell","sequence":"additional","affiliation":[{"name":"Institute for Clean Growth and Future Mobility, Coventry University, Coventry CV1 5FB, UK"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,16]]},"reference":[{"key":"ref_1","unstructured":"On-Road Automated Driving (ORAD) Committee (2014). 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