Analyzing Driver Drowsiness: From Causes to Effects

Soares, Sónia; Monteiro, Tiago; Lobo, António; Couto, António; Cunha, Liliana; Ferreira, Sara

doi:10.3390/su12051971

Cited by 34 publications

(21 citation statements)

References 34 publications

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“…The transition from awake to asleep is recognized as sleep onset (SO) [ 1 ], commonly known as drowsiness. Driver drowsiness results in over 20% of road accidents [ 2 , 3 ], reported as one of the leading causes of road fatalities. The most common factors associated with driver drowsiness are sleep deprivation, duration of driving, monotonous environments, drug and alcohol use, and chronic sleepiness [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Microneedle Array Electrode-Based Wearable EMG System for Detection of Driver Drowsiness through Steering Wheel Grip

Satti

Kim

et al. 2021

Sensors

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Driver drowsiness is a major cause of fatal accidents throughout the world. Recently, some studies have investigated steering wheel grip force-based alternative methods for detecting driver drowsiness. In this study, a driver drowsiness detection system was developed by investigating the electromyography (EMG) signal of the muscles involved in steering wheel grip during driving. The EMG signal was measured from the forearm position of the driver during a one-hour interactive driving task. Additionally, the participant’s drowsiness level was also measured to investigate the relationship between muscle activity and driver’s drowsiness level. Frequency domain analysis was performed using the short-time Fourier transform (STFT) and spectrogram to assess the frequency response of the resultant signal. An EMG signal magnitude-based driver drowsiness detection and alertness algorithm is also proposed. The algorithm detects weak muscle activity by detecting the fall in EMG signal magnitude due to an increase in driver drowsiness. The previously presented microneedle electrode (MNE) was used to acquire the EMG signal and compared with the signal obtained using silver-silver chloride (Ag/AgCl) wet electrodes. The results indicated that during the driving task, participants’ drowsiness level increased while the activity of the muscles involved in steering wheel grip decreased concurrently over time. Frequency domain analysis showed that the frequency components shifted from the high to low-frequency spectrum during the one-hour driving task. The proposed algorithm showed good performance for the detection of low muscle activity in real time. MNE showed highly comparable results with dry Ag/AgCl electrodes, which confirm its use for EMG signal monitoring. The overall results indicate that the presented method has good potential to be used as a driver’s drowsiness detection and alertness system.

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Section: Introductionmentioning

confidence: 99%

Microneedle Array Electrode-Based Wearable EMG System for Detection of Driver Drowsiness through Steering Wheel Grip

Satti

Kim

et al. 2021

Sensors

View full text Add to dashboard Cite

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“…These findings are not surprising because our physiological clock prompts sleep at those moments. Recent studies have produced large amounts of evidence focusing their fundamental perspective and potential applications related to driver drowsiness and alertness levels [21][22][23]. New challenges incorporate not only detecting drowsiness but also predicting the driver's state in upcoming moments by predicting future values following the trends and environment variables.…”

Section: Introductionmentioning

confidence: 99%

A Drowsiness Reduction Strategy Utilizing Visual Stimulation With Different Colors of Light: An fNIRS Study

et al. 2021

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Drowsiness during driving is a severe problem that must be addressed to improve road safety. Numerous counter-measures have been proposed to resolve this issue like adaptive environmental settings (temperature, sound, and light). The objective of this study was to accurately predict the effects of exposure to different colors of light on human drowsiness by using functional near-infrared spectroscopy and other physical measurements (heart rate and eye closure). We targeted two regions of the brain (visual and prefrontal cortices). Twenty-three healthy subjects were investigated to evaluate all variables related to the awakening state, and twenty-one healthy subjects were also examined in the drowsy state evaluation. Eventually, the ten most suitable subjects were exposed to red, green, and blue lights under drowsy conditions, according to the experimental paradigm. Dim light was maintained in the experimental premises before and after colored light exposure to limit the results to those produced only in response to the desired stimuli. Eye closure, heart rate, and changes in oxy and deoxy hemoglobin concentrations were measured to characterize the condition (awake/drowsy) of the subject. A support vector machine classifier was used to identify the classification accuracy of awake and drowsy states. In conclusion, exposure to blue light triggered the activation of oxy hemoglobin in targeted brain regions; however, deoxy hemoglobin was not significantly affected by exposure to any of the colored lights. Noticeably, our study revealed that blue light exposure is more effective at reducing drowsiness than exposure to red and green lights.INDEX TERMS functional near-infrared spectroscopy, colored light exposure, drowsiness, sleep deprivation, heart rate, and eye closure.

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“…Transportation is one of the most important areas in many sectors. In the transportation industry, fatigue in truck drivers is generally identified as the main safety issue because it has consistently been linked to road crashes [1][2][3][4][5][6]. A transportation department study from the United States reported that three independent studies identified lack of alertness or driving fatigue as one of the main reasons for serious accidents [3].…”

Section: Introductionmentioning

confidence: 99%

Impact of Safety Culture Implementation on Driving Performance among Oil and Gas Tanker Drivers: A Partial Least Squares Structural Equation Modelling (PLS-SEM) Approach

et al. 2021

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This research aims to develop a safety culture model by investigating the relationship between safety culture and driving performance. In previous studies, safety culture has been one of the factors that determine safety issues. These issues were then contextually transformed via a pilot study and organized in the form of a theoretical model. The data were collected from 307 oil and gas tanker drivers in Malaysia through questionnaire surveys. Consequently, structural equation models of partial least squares (PLS-SEM) were applied to statistically assess the final model of this study. The results showed that the implementation of safety culture contributes to driving performance at a substantial level; there is a strong association with an effect of 67.3%. The findings of this research would serve as a benchmark for decision-makers in the oil and gas transportation sector, as promoting an awareness of safety culture should boost the efficiency of drivers. This research fills a gap in knowledge by identifying that positive safety culture practices and mindset are direct antecedents for the improvement of driver performance and, thus, the avoidance of road accidents.

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Analyzing Driver Drowsiness: From Causes to Effects

Cited by 34 publications

References 34 publications

Microneedle Array Electrode-Based Wearable EMG System for Detection of Driver Drowsiness through Steering Wheel Grip

Microneedle Array Electrode-Based Wearable EMG System for Detection of Driver Drowsiness through Steering Wheel Grip

A Drowsiness Reduction Strategy Utilizing Visual Stimulation With Different Colors of Light: An fNIRS Study

Impact of Safety Culture Implementation on Driving Performance among Oil and Gas Tanker Drivers: A Partial Least Squares Structural Equation Modelling (PLS-SEM) Approach

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