Sex Differences in Time-Domain and Frequency-Domain Heart Rate Variability Measures of Fatigued Drivers.

Chao Zeng,Bo Cheng,Chaoyang Chen,Wenjun Wang,Chaofei Zhang

doi:10.3390/ijerph17228499

Abstract

The effects of fatigue on a driver’s autonomic nervous system (ANS) were investigated through heart rate variability (HRV) measures considering the difference of sex. Electrocardiogram (ECG) data from 18 drivers were recorded during a simulator-based driving experiment. Thirteen short-term HRV measures were extracted through time-domain and frequency-domain methods. First, differences in HRV measures related to mental state (alert or fatigued) were analyzed in all subjects. Then, sex-specific changes between alert and fatigued states were investigated. Finally, sex differences between alert and fatigued states were compared. For all subjects, ten measures showed significant differences (Mann-Whitney U test, p < 0.01) between different mental states. In male and female drivers, eight and four measures, respectively, showed significant differences between different mental states. Six measures showed significant differences between males and females in an alert state, while ten measures showed significant sex differences in a fatigued state. In conclusion, fatigue impacts drivers’ ANS activity, and this impact differs by sex; more differences exist between male and female drivers’ ANS activity in a fatigued state than in an alert state.

Highlights

It has been reported that nearly 1.3 million people are killed and 50 million people are injured in road traffic collisions each year [1], and driving fatigue is estimated to be responsible for 20–30% of all road fatalities [2,3,4]
With being aware of the limitations in this field, the aim of the study was three-fold: First, as many heart rate variability (HRV) measures as possible were extracted using time domain and frequency domain methods to provide a comprehensive evaluation of the impact of fatigue on the driver’s autonomic nervous system (ANS) and to provide references for the development of driving fatigue detection methods; second, the HRV measures of drivers of different sexes in different mental states were compared to provide a basis for developing driver-specific fatigue detection algorithms for specific sexes; and the similarities and differences of HRV measures of males and females in both an alert and a fatigued state were compared to provide a new perspective for understanding the sex differences in the ANS
This study investigated the effects of both mental states and sex factors on drivers’ ANSs by extracting thirteen time and frequency domain HRV measures from ECG signals

Summary

Introduction

It has been reported that nearly 1.3 million people are killed and 50 million people are injured in road traffic collisions each year [1], and driving fatigue is estimated to be responsible for 20–30% of all road fatalities [2,3,4]. There are many psychophysiological symptoms such as tiredness, lack of energy, difficulties to concentrate, loss of interest, and so on, caused by fatigue that dangerously affect driving [7]. Driving requires mental and physical attention and alertness to be performed effectively [8], and fatigue may affect a driver’s attention and vigilance when controlling a vehicle and may result in a disastrous consequence [9]. Predicting a driver’s mental state by measuring his or her fatigue before or during driving is a method that may be used to reduce traffic accidents [9]. Vehicle-based methods detect the level of a driver’s fatigue usually by steering wheel movement or standard deviation in the lane position

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Discussion

Conclusion