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REVIEW article

Front. Comput. Neurosci.
Volume 18 - 2024 | doi: 10.3389/fncom.2024.1475530
This article is part of the Research Topic 15 Years of Frontiers in Computational Neuroscience - Computational Motor Control View all 4 articles

Systematic Review of Cognitive Impairment in Drivers Through Mental Workload Using Physiological Measures of Heart Rate Variability

Provisionally accepted
Mansoor Raza Mansoor Raza 1*Mohsin Murtaza Mohsin Murtaza 1Chi-Tsun Cheng Chi-Tsun Cheng 1Muhana Muslam Muhana Muslam 2Bader M. Albahla Bader M. Albahla 2
  • 1 RMIT University, Melbourne, Australia
  • 2 Imam Muhammad ibn Saud Islamic University, Riyadh, Saudi Arabia

The final, formatted version of the article will be published soon.

    The intricate interplay between driver cognitive dysfunction, mental workload (MWL), and heart rate variability (HRV) provides a captivating avenue for investigation within the domain of transportation safety studies. This article provides a systematic review and examines cognitive hindrance stemming from mental workload and heart rate variability. It scrutinizes the mental workload experienced by drivers by leveraging data gleaned from prior studies that employed heart rate monitoring systems and eye tracking technology, thereby illuminating the correlation between cognitive impairment, mental workload, and physiological indicators such as heart rate and ocular movements. The investigation is grounded in the premise that the mental workload of drivers can be assessed through physiological cues, such as heart rate and eye movements. The study discovered that heart rate variability (HRV) and infrared (IR) measurements played a crucial role in evaluating fatigue and workload for skilled drivers. However, the study overlooked potential factors contributing to cognitive impairment in drivers and could benefit from incorporating alternative indicators of cognitive workload for deeper insights. Furthermore, investigated driving simulators demonstrated that an eco-safe driving Human-Machine Interface (HMI) significantly promoted safe driving behaviours without imposing excessive mental and visual workload on drivers. Recommendations were made for future studies to consider additional indicators of cognitive workload, such as subjective assessments or task performance metrics, for a more comprehensive understanding.

    Keywords: Mental workload (MWL), heart rate variability (HRV), take over request (TOR), society of automotive engineers (SAE), driver cognitive impairment, Human machine interface (HMI), eye tracking, Driver safety

    Received: 04 Aug 2024; Accepted: 17 Oct 2024.

    Copyright: © 2024 Raza, Murtaza, Cheng, Muslam and Albahla. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Mansoor Raza, RMIT University, Melbourne, Australia

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.