Evaluation of driver drowsiness by trained raters

Wierwille, Walter W.; Ellsworth, Lynne A.

doi:10.1016/0001-4575(94)90019-1

Cited by 296 publications

(188 citation statements)

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“…These include driverrelated physiological measures, such as ocular measures, including blink duration and slow eyelid closures (Wierwille & Ellsworth, 1994;Åkerstedt, Peters, Anund, & Keckland, 2005;Anund et al, 2008;Åkerstedt et al, 2010) and electroencephalography (EEG) algorithms (Cajochen et al, 1999;Horne & Reyner, 1996), or vehicle-related measures, such as lane departure measures (May & Baldwin, 2009;Mortazavi, Eskandarian, & Sayed, 2009). Eyelid closure appears to be a promising method for indicating driver drowsiness in real-time (Dinges, Mallis, Maislan, & Walker-Powell, 1999;Ftouni et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…As slow eyelid closure is observed to precede sleep onset, this physiological response has been examined as a potential leading indicator of sleepiness in active individuals (Santamaria & Chiappa, 1987). The metric "PERCLOS" is assessed as the percentage of time that the eyes are 80% closed (Wierwille & Ellsworth, 1994). Manually scored PERCLOS was originally developed using video recordings of the face in sleep-deprived, truck drivers, during a simulated driving task, and was found to be a valid predictor of drowsiness (Wierwille & Ellsworth, 1994).…”

Section: Introductionmentioning

confidence: 99%

“…The metric "PERCLOS" is assessed as the percentage of time that the eyes are 80% closed (Wierwille & Ellsworth, 1994). Manually scored PERCLOS was originally developed using video recordings of the face in sleep-deprived, truck drivers, during a simulated driving task, and was found to be a valid predictor of drowsiness (Wierwille & Ellsworth, 1994). One laboratory experiment assessed six different drowsiness detection technologies, including eye blink monitors, EEG monitoring, head position monitors and video-scored PERCLOS under conditions of 42 hours of sleep deprivation (Dinges, Mallis, Maislan, & Walker-Powell, 1998).…”

Section: Introductionmentioning

confidence: 99%

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Slow eyelid closure as a measure of driver drowsiness and its relationship to performance

Jackson

Raj

Croft

et al. 2016

Traffic Injury Prevention

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(2016). Slow eyelid closure as a measure of driver drowsiness and its relationship to performance. Traffic Injury Prevention, 17 (3), 251-257. Slow eyelid closure as a measure of driver drowsiness and its relationship to performance AbstractObjective: Slow eyelid closure is recognized as an indicator of sleepiness in sleep-deprived individuals, although automated ocular devices are not well validated. This study aimed to determine whether changes in eyelid closure are evident following acute sleep deprivation as assessed by an automated device and how ocular parameters relate to performance after sleep deprivation. Methods: Twelve healthy professional drivers (45.58 ± 10.93 years) completed 2 randomized sessions: After a normal night of sleep and after 24 h of total sleep deprivation. Slow eye closure (PERCLOS) was measured while drivers performed a simulated driving task. Results: Following sleep deprivation, drivers displayed significantly more eyelid closure (P < .05), greater variation in lane position (P < .01) and more attentional lapses (P < .05) compared to after normal sleep. PERCLOS was moderately associated with variability in both vigilance performance (r = 0.68, P < .05) and variation in lane position on the driving task (r = 0.61, P < .05). Conclusions: Automated ocular measurement appears to be an effective means of detecting impairment due to sleep loss in the laboratory.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Slow eyelid closure as a measure of driver drowsiness and its relationship to performance

Jackson

Raj

Croft

et al. 2016

Traffic Injury Prevention

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show abstract

“…Video coding was performed to distinguish any lane departures not associated with drowsiness. For each lane departure flagged in the data stream, a researcher rated the preceding 60 s of video using the Objective Rating of Drowsiness Scale (Wierwille and Ellsworth 1994). Lane departures where the driver was coded at level 2 or above were classified as drowsy lane departures.…”

Section: Methodsmentioning

confidence: 99%

“…Interventions that reduce the risk of drowsy lane departures therefore have the greatest potential safety benefit. Therefore, lane departures where the driver was rated as drowsy using the Objective Rating of Drowsiness Scale (Wierwille and Ellsworth 1994) were used to define drowsy driving events to test countermeasure effectiveness. If countermeasures are effective at warning drivers or keeping them alert, we expected a reduction in drowsy lane departures and standard deviation in lateral position (SDLP) relative to a no-countermeasure group.…”

Section: Introductionmentioning

confidence: 99%

Evaluating driver drowsiness countermeasures

Gaspar

Brown

Schwarz

et al. 2017

Traffic Injury Prevention

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Objective: Driver drowsiness contributes to a substantial number of fatal and nonfatal crashes, with recent estimates attributing up to 21% of fatal crashes to drowsiness. This article describes recent NHTSA research on in-vehicle drowsiness countermeasures. Recent advances in technology and state detection algorithms have shown success in detecting drowsiness using a variety of data sources, including camera-based eye tracking, steering wheel position, yaw rate, and vehicle lane position. However, detection is just the first step in reducing drowsy driving crashes. Countermeasures are also needed to provide feedback to the driver, modify driver behavior, and prevent crashes. The goal of this study was to evaluate the effectiveness of in-vehicle drowsiness countermeasures in reducing drowsy lane departures. The tested countermeasures included different warning modalities in either a discrete or staged interface. Methods: Data were collected from 72 young adult drivers (age 21-32) in the high-fidelity full-motion National Advanced Driving Simulator. Drivers completed a 45-min simulated nighttime drive at 2 time points, late night and early morning, where drowsiness was manipulated by continuous hours awake. Fortyeight drivers were exposed to one of 6 countermeasures that varied along 2 dimensions, type and modality. The countermeasures relied on a steering-based drowsiness detection algorithm developed in prior NHTSA research. Twenty-four drivers received no countermeasure and were used as a baseline comparison. System effectiveness was measured by lane departures and standard deviation in lateral position (SDLP). Results: There was a reduction in drowsy lane departure frequency and lane position variability for drivers with countermeasures compared to the baseline no-countermeasure group. Importantly, the data suggest that multistage alerts, which provide an indication of increasing urgency, were more effective in reducing drowsy lane departures than single-stage discrete alerts, particularly during early morning drives when drivers were drowsier. Conclusions:The results indicate that simple in-vehicle countermeasures, such as an auditory-visual coffee cup icon, can reduce the frequency of drowsy lane departures in the context of relatively short drives. An important next step is to evaluate the impact of drowsiness countermeasures in the context of longer, multiple-hour drives. In these cases, it may not be possible to keep drivers awake via feedback warnings and it is important to understand whether countermeasures prompt drivers to stop to rest. The next phase of this research project will examine the role of drowsiness countermeasures over longer drives using a protocol that replicates the motivational conditions of drowsy driving.

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Highly‐Sensitive Skin‐Attachable Eye‐Movement Sensor Using Flexible Nonhazardous Piezoelectric Thin Film

Kim

Chen

Wang

et al. 2020

Adv Funct Materials

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Accurate and continuous monitoring of eye movements using compact, low‐power‐consuming, and easily‐wearable sensors is necessary in personal and public health and safety, selected medical diagnosis techniques (point‐of‐care diagnostics), and personal entertainment systems. In this study, a highly sensitive, noninvasive, and skin‐attachable sensor made of a stable flexible piezoelectric thin film that is also free of hazardous elements to overcome the limitations of current computer‐vision‐based eye‐tracking systems and piezoelectric strain sensors is developed. The sensor fabricated from single‐crystalline III‐N thin film by a layer‐transfer technique is highly sensitive and can detect subtle movements of the eye. The flexible eye movement sensor converts the mechanical deformation (skin deflection by eye blinking and eyeball motion) with various frequencies and levels into electrical outputs. The sensor can detect abnormal eye flickering and conditions caused by fatigue and drowsiness, including overlong closure, hasty eye blinking, and half‐closed eyes. The abnormal eyeball motions, which may be the sign of several brain‐related diseases, can also be measured, as the sensor generates discernable output voltages from the direction of eyeball movements. This study provides a practical solution for continuous sensing of human eye blinking and eyeball motion as a critical part of personal healthcare, safety, and entertainment systems.

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Evaluation of driver drowsiness by trained raters

Cited by 296 publications

References 5 publications

Slow eyelid closure as a measure of driver drowsiness and its relationship to performance

Slow eyelid closure as a measure of driver drowsiness and its relationship to performance

Evaluating driver drowsiness countermeasures

Highly‐Sensitive Skin‐Attachable Eye‐Movement Sensor Using Flexible Nonhazardous Piezoelectric Thin Film

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