IMR Press / RCM / Volume 22 / Issue 3 / DOI: 10.31083/j.rcm2203090
Open Access Systematic Review
Accurate and early detection of sleepiness, fatigue and stress levels in drivers through Heart Rate Variability parameters: a systematic review
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1 ‘Grigore T. Popa’ University of Medicine and Pharmacy, 700115 Iasi, Romania
2 Department of Interventional Cardiology - Cardiovascular Diseases Institute, 700503 Iasi, Romania
3 Academy of Medical Sciences, 030167 Bucharest, Romania
4 Tehnical University of Iasi ‘Gheorghe Asachi’, 700050 Iasi, Romania
5 GreenSoft Ltd, 700137 Iasi, Romania
6 Nephrology Clinic, Dialysis, and Renal Transplant Center—‘C.I. Parhon’ University Hospital, 700503 Iasi, Romania
These authors contributed equally.
Rev. Cardiovasc. Med. 2021 , 22(3), 845–852; https://doi.org/10.31083/j.rcm2203090
Submitted: 8 July 2021 | Revised: 17 July 2021 | Accepted: 26 July 2021 | Published: 24 September 2021
Abstract

Sleepiness, fatigue, and stress in drivers are the leading causes of car crashes. In the late two decades, there is an endeavor to monitor vital signs, stress levels, and fatigue using adapted sensors supported by technological advances. To the best of our knowledge, this systematic review is the first to investigate the role of HRV measurement for sleepiness, fatigue, and stress level monitoring in car drivers. A search was performed in PubMed, Embase, and Cochrane databases using prespecified keywords. Studies were considered for inclusion if they reported original data regarding the association between different HRV measurements and drivers’ sleepiness, fatigue, or stress levels. Of the retrieved 749 citations, 19 studies were finally included. The sensibility and specificity of HRV significantly varied across studies, respectively 47.1%–95% and 74.6%–98%. Accuracy was also different, ranging from 56.6% to 95%. Nevertheless, in real-world conditions, confounding factors could affect sympathovagal tone and HRV. Multiple HRV parameters measurement rather than one parameter approach seems to be the optimal strategy for evaluating the vigilance state in drivers that it would be possible to achieve a good performance. As all studies were observational, data should be confirmed in randomized controlled trials. In conclusion, HRV represents a potentially valuable marker for sleepiness, fatigue, and stress monitoring in car drivers. HRV measurements could be implemented in future clinical models and sensors to detect early sleepiness and fatigue and prevent car crashes. More studies with larger populations are needed to support this evidence.

Keywords
Heart rate variability
Drivers
Fatigue
Sleepiness
Stress detection
Systematic review
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