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Systematic review protocol on mobile physiological monitoring systems for driver fatigue detection

  • Driving safety is an important matter that, if violated, can have serious consequences such as injury or even death. Several studies have shown that fatigue, and the drowsiness that often results from it, has a significant impact on road safety. It is therefore essential to detect the symptoms of fatigue at an early stage so that appropriate countermeasures can be taken before a dangerous situation arises. Various systems can be used to detect fatigue, including those that monitor physiological signals and look for specific patterns to detect changes and trigger appropriate action if necessary. Mobile systems, which offer greater flexibility, are the focus of some of these efforts. In order to facilitate a methodological approach in the development of new systems, it is imperative to obtain a systematic overview within the initial phase. This enables the identification of both established and promising approaches, as well as the identification of actual gaps that necessitate further research. The aim of this article is to set out a protocol for the conduct of a systematic review in order to be able to subsequently carry it out. This includes researching and defining features such as eligibility criteria, selecting appropriate databases, search strategies and, most importantly, defining the specific research question. The result of this work is a clear and methodologically prepared summary of the most important points to be considered when conducting the systematic review on the subject of ”Mobile Physiological Monitoring Systems for Driver Fatigue Detection”.

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Metadaten
Author of HS ReutlingenMartínez Madrid, Natividad
URN:urn:nbn:de:bsz:rt2-opus4-59366
DOI:https://doi.org/10.1016/j.procs.2025.10.028
ISSN:1877-0509
Published in:Procedia Computer Science
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Journal article
Language:English
Publication year:2025
Volume:270
Issue:29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025)
Page Number:8
First Page:5599
Last Page:5606
DDC classes:004 Informatik
Open access?:Ja
Licence (German):License Logo  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International