The impact of alcohol consumption on commercial eye blink drowsiness detection technology.

INTRODUCTION: Driver drowsiness detection technology that assesses eye blinks is increasingly being used as a safety intervention in the transport industry. It is unclear how alcohol consumption to common legal driving limits impacts upon this technology. The aim of the study was to assess the impact of a blood alcohol content (BAC) of 0.05% and of 0.08% on drowsiness detection technology during simulated driving. METHODS: Participants completed a 60-min driving simulation and sleepiness questionnaire under three conditions: 1-0.00% BAC, 2-0.05% BAC and 3-0.08% BAC. During the driving simulation task participants wore a commercial eye blink drowsiness detection technology (Optalert) with the drowsiness alarms silenced. RESULTS: Twelve participants (3 female) completed all alcohol conditions. Relative to baseline, all eye blink parameters were affected at 0.08% BAC (all p < 0.05), whereas 0.05% BAC only affected the composite eye blink drowsiness measure (the Johns Drowsiness Scale). CONCLUSIONS: Alcohol consumption to 0.08% BAC impaired eye blink measures to a level that would be considered a moderate drowsiness risk. Therefore, employers should be aware that drowsiness alerts from these technologies may increase after alcohol consumption.

A brief assessment of eye blink drowsiness immediately prior to or following driving detects drowsiness related driving impairment.

Drowsy driving is a major cause of fatal and serious injury motor vehicle accidents. The inability objectively to assess drowsiness has hindered the assessment of fitness to drive and the development of drowsy driving regulations. This study evaluated whether spontaneous eye blink parameters measured briefly pre- and post-drive could be used to detect drowsy driving impairment. Twelve healthy participants (6 female) drove an instrumented vehicle for 2 h on a closed-loop track during a rested (8-10 h awake) and an extended wake condition (32-34 h awake). Pre- and post-drive, the participants completed a 5 min eye blink task, a psychomotor vigilance task (PVT), and the Karolinska sleepiness scale (KSS). Whole drive impairment was defined as >3.5 lane departures per hour. Severe end of drive impairment was defined as ≥2 lane departures in the last 15 min. The pre-drive % of time with eyes closed best predicted the whole drive impairment (area under the curve [AUC] 0.87). KSS had similar prediction ability (AUC 0.85), while PVT reaction time (AUC 0.72) was less accurate. The composite eye blink parameter, the Johns drowsiness scale was the best retrospective detector of severe end of drive impairment (AUC 0.99). The PVT reaction time (AUC 0.92) and the KSS (AUC 0.93) were less accurate. Eye blink parameters detected drowsy driving impairment with an accuracy that was similar to, or marginally better than, PVT and KSS. As eye blink measures are simple to measure, are objective and have high accuracy, they present an ideal option for the assessment of fitness for duty and roadside drowsiness.

Eye blink parameters to indicate drowsiness during naturalistic driving in participants with obstructive sleep apnea: A pilot study.

OBJECTIVES: To determine whether continuous eye blink measures could identify drowsiness in patients with obstructive sleep apnea (OSA) during a week of naturalistic driving. DESIGN: Observational study comparing OSA patients and healthy controls. SETTING: Regular naturalistic driving across one week. PARTICIPANTS: Fifteen untreated moderate to severe OSA patients and 15 age (± 5 years) and sex (female = 6) matched healthy controls. MEASUREMENTS: Participants wore an eye blink drowsiness recording device during their regular driving for one week. RESULTS: During regular driving, the duration of time with no ocular movements (quiescence), was elevated in the OSA group by 43% relative to the control group (mean [95% CI] 0.20[0.17, 0.25] vs 0.14[0.12, 0.18] secs, P = .011). During long drives only, the Johns Drowsiness Scale was also elevated and increased by 62% in the OSA group relative to the control group (1.05 [0.76, 1.33] vs 0.65 [0.36, 0.93], P = .0495). Across all drives, critical drowsiness events (defined by a Johns Drowsiness Scale score ≥2.6) were twice as frequent in the OSA group than the control group (rate ratio [95% CI] =1.93 [1.65, 2.25], P ≤ .001). CONCLUSIONS: OSA patients were drowsier than healthy controls according to some of the continuous real time eye blink drowsiness measures. The findings of this pilot study suggest that there is potential for eye blink measures to be utilized to assess fitness to drive in OSA patients. Future work should assess larger samples, as well as the relationship of eye blink measures to conventional fitness to drive assessments and crash risk.

Assessing the validity of eyelid parameters to detect impairment due to benzodiazepines.

OBJECTIVE: Benzodiazepines impair driving ability and psychomotor function. Eyelid parameters accurately reflect drowsiness; however, the effects of benzodiazepines on these measures have not been extensively studied. The aim of this study was to investigate the effect of benzodiazepines on eyelid parameters and evaluate their accuracy for detecting psychomotor impairment. METHODS: Eyelid parameters were recorded during a psychomotor vigilance task (PVT) and driving simulation over 2 days, baseline, and after 20-mg oral temazepam. The utility of eyelid parameters for detecting PVT lapses was evaluated using receiver operating characteristic curves, and cut-off levels indicating impairment (≥1 and ≥2 PVT lapses per min) were identified. The accuracy of these cut-off levels for detecting driving simulator crashes was then examined. RESULTS: PVT and driving simulator performance was significantly impaired following benzodiazepine administration (p < .05). Average eyelid closure duration (inter-event duration) was a reliable indicator of PVT lapses (area under the curve [AUC] of 0.87-0.90). The cut-off value of eyelid closure duration derived from PVT AUC was able to predict driving simulator crashes with moderately high sensitivity and specificity (76.23% and 75.00%). CONCLUSIONS: Eyelid parameters were affected by benzodiazepines and accurately detected the psychomotor impairment. In particular, eyelid closure duration is a promising real-time indicator of benzodiazepine impairment.

Eye-Blink Parameters Detect On-Road Track-Driving Impairment Following Severe Sleep Deprivation.

STUDY OBJECTIVES: Drowsiness leads to 20% of fatal road crashes, while inability to assess drowsiness has hampered drowsiness interventions. This study examined the accuracy of eye-blink parameters for detecting drowsiness related driving impairment in real time. METHODS: Twelve participants undertook two sessions of 2-hour track-driving in an instrumented vehicle following a normal night's sleep or 32 to 34 hours of extended wake in a randomized crossover design. Eye-blink parameters and lane excursion events were monitored continuously. RESULTS: Sleep deprivation increased the rates of out-of-lane driving events and early drive terminations. Episodes of prolonged eyelid closures, blink duration, the ratio of amplitude to velocity of eyelid closure, and John's Drowsiness Score (JDS, a composite score) were also increased following sleep deprivation. A time-on-task (drive duration) effect was evident for out-of-lane events rate and most eye-blink parameters after sleep deprivation. The JDS demonstrated the strongest association with the odds of out-of-lane events in the same minute, whereas measures of blink duration and prolonged eye closure were stronger indicators of risk for out-of-lane events over longer periods of 5 minutes and 15 minutes, respectively. Eye-blink parameters also achieved moderate accuracies (specificities from 70.12% to 84.15% at a sensitivity of 50%) for detecting out-of-lane events in the same minute, with stronger associations over longer timeframes of 5 minutes to 15 minutes. CONCLUSIONS: Eyelid closure parameters are useful tools for monitoring and predicting drowsiness-related driving impairment (out-of-lane events) that could be utilized for monitoring drowsiness and assessing the efficacy of drowsiness interventions. CLINICAL TRIAL REGISTRATION: This study is registered with the Australian New Zealand Clinical Trial Registry (ANCTR), http://www.anzctr.org.au/TrialSearch.aspx ACTRN12612000102875. CITATION: Shekari Soleimanloo S, Wilkinson VE, Cori JM,Westlake J, Stevens B, Downey LA, Shiferaw BA, Rajaratnam SMW, Howard ME. Eye-blink parameters detect on-road track-driving impairment following severe sleep deprivation. J Clin Sleep Med. 2019;15(9):1271-1284.

The Differential Effects of Regular Shift Work and Obstructive Sleep Apnea on Sleepiness, Mood and Neurocognitive Function.

STUDY OBJECTIVES: To assess whether poor sleep quality experienced by regular shift workers and individuals with obstructive sleep apnea (OSA) affects neurobehavioral function similarly, or whether the different etiologies have distinct patterns of impairment. METHODS: Thirty-seven shift workers (> 24 hours after their last shift), 36 untreated patients with OSA, and 39 healthy controls underwent assessment of sleepiness (Epworth Sleepiness Scale [ESS]), mood (Beck Depression Index, State Trait Anxiety Inventory [STAI], Profile of Mood States), vigilance (Psychomotor Vigilance Task [PVT], Oxford Sleep Resistance Test [OSLER], driving simulation), neurocognitive function (Logical Memory, Trails Making Task, Digit Span Task, Victoria Stroop Test) and polysomnography. RESULTS: Sleepiness (ESS score; median, interquartile range) did not differ between the OSA (10.5, 6.3-14) and shift work (7, 5-11.5) groups, but both had significantly elevated scores relative to the control group (5, 3-6). State anxiety (STAI-S) was the only mood variable that differed significantly between the OSA (35, 29-43) and shift work (30, 24-33.5) groups, however both demonstrated several mood deficits relative to the control group. The shift work and control groups performed similarly on neurobehavioral tasks (simulated driving, PVT, OSLER and neurocognitive tests), whereas the OSA group performed worse. On the PVT, lapses were significantly greater for the OSA group (3, 2-6) than both the shift work (2, 0-3.5) and control (1, 0-4) groups. CONCLUSIONS: Shift workers and patients with OSA had similar sleepiness and mood deficits relative to healthy individuals. However, only the patients with OSA showed deficits on vigilance and neurocognitive function relative to healthy individuals. These findings suggest that distinct causes of sleep disturbance likely result in different patterns of neurobehavioral dysfunction.

Stationary gaze entropy predicts lane departure events in sleep-deprived drivers.

Performance decrement associated with sleep deprivation is a leading contributor to traffic accidents and fatalities. While current research has focused on eye blink parameters as physiological indicators of driver drowsiness, little is understood of how gaze behaviour alters as a result of sleep deprivation. In particular, the effect of sleep deprivation on gaze entropy has not been previously examined. In this randomised, repeated measures study, 9 (4 male, 5 female) healthy participants completed two driving sessions in a fully instrumented vehicle (1 after a night of sleep deprivation and 1 after normal sleep) on a closed track, during which eye movement activity and lane departure events were recorded. Following sleep deprivation, the rate of fixations reduced while blink rate and duration as well as saccade amplitude increased. In addition, stationary and transition entropy of gaze also increased following sleep deprivation as well as with amount of time driven. An increase in stationary gaze entropy in particular was associated with higher odds of a lane departure event occurrence. These results highlight how fatigue induced by sleep deprivation and time-on-task effects can impair drivers' visual awareness through disruption of gaze distribution and scanning patterns.

Identifying who will benefit from non-invasive ventilation in amyotrophic lateral sclerosis/motor neurone disease in a clinical cohort.

BACKGROUND: Respiratory failure is associated with significant morbidity and is the predominant cause of death in motor neurone disease/amyotrophic lateral sclerosis (MND/ALS). This study aimed to determine the effect of non-invasive ventilatory (NIV) support on survival and pulmonary function decline across MND/ALS phenotypes. METHODS: Cohort recruited via a specialist, multidisciplinary clinic. Patients were categorised into four clinical phenotypes (ALS, flail arm, flail leg and primary lateral sclerosis) according to site of presenting symptom and the pattern of upper versus lower motor neurone involvement. NIV was initiated according to current consensus practice guidelines. RESULTS: Between 1991 and 2011, 1198 patients diagnosed with ALS/MND were registered. 929 patients (77.5%) fulfilled the selection criteria and their data were analysed. Median tracheostomy free survival from symptom onset was 28 months in NIV-treated patients compared to 15 months in untreated (Univariate Cox regression HR=0.61 (0.51 to 0.73), p<0.001). The positive survival effect of NIV persisted when the model was adjusted for age, gender, riluzole and percutaneous endoscopic gastrostomy use (HR=0.72 (0.60 to 0.88, p=0.001). In contrast with the only randomised controlled trial, NIV statistically significantly increased survival by 19 months in those with ALS-bulbar onset (Univariate HR=0.50 (0.36 to 0.70), multivariate HR=0.59 (0.41 to 0.83)). These data confirm that NIV improves survival in MND/ALS. The overall magnitude of benefit is 13 months and was largest in those with ALS-bulbar disease. Future research should explore the optimal timing of NIV initiation within phenotypes in order to optimise respiratory function, quality of life and survival.

Specific sleepiness symptoms are indicators of performance impairment during sleep deprivation.

Drivers are not always aware that they are becoming impaired as a result of sleepiness. Using specific symptoms of sleepiness might assist with recognition of drowsiness related impairment and help drivers judge whether they are safe to drive a vehicle, however this has not been evaluated. In this study, 20 healthy volunteer professional drivers completed two randomized sessions in the laboratory - one under 24h of acute sleep deprivation, and one with alcohol. The Psychomotor Vigilance Task (PVT) and a 30min simulated driving task (AusEdTM) were performed every 3-4h in the sleep deprivation session, and at a BAC of 0.00% and 0.05% in the alcohol session, while electroencephalography (EEG) and eye movements were recorded. After each test session, drivers completed the Karolinska Sleepiness Scale (KSS) and the Sleepiness Symptoms Questionnaire (SSQ), which includes eight specific sleepiness and driving performance symptoms. A second baseline session was completed on a separate day by the professional drivers and in an additional 20 non-professional drivers for test-retest reliability. There was moderate test-retest agreement on the SSQ (r=0.59). Significant correlations were identified between individual sleepiness symptoms and the KSS score (r values 0.50-0.74, p<0.01 for all symptoms). The frequency of all SSQ items increased during sleep deprivation (χ(2) values of 28.4-80.2, p<0.01 for all symptoms) and symptoms were related to increased subjective sleepiness and performance deterioration. The symptoms "struggling to keep your eyes open", "difficulty maintaining correct speed", "reactions were slow" and "head dropping down" were most closely related to increased alpha and theta activity on EEG (r values 0.49-0.59, p<0.001) and "nodding off to sleep" and "struggling to keep your eyes open" were related to slow eye movements (r values 0.67 and 0.64, p<0.001). Symptoms related to visual disturbance and impaired driving performance were most accurate at detecting severely impaired driving performance (AUC on ROC curve of 0.86-0.91 for detecting change in lateral lane position greater than the change at a BAC of 0.05%). Individual sleepiness symptoms are related to impairment during acute sleep deprivation and might be able to assist drivers in recognizing their own sleepiness and ability to drive safely.

The accuracy of eyelid movement parameters for drowsiness detection.

STUDY OBJECTIVES: Drowsiness is a major risk factor for motor vehicle and occupational accidents. Real-time objective indicators of drowsiness could potentially identify drowsy individuals with the goal of intervening before an accident occurs. Several ocular measures are promising objective indicators of drowsiness; however, there is a lack of studies evaluating their accuracy for detecting behavioral impairment due to drowsiness in real time. METHODS: In this study, eye movement parameters were measured during vigilance tasks following restricted sleep and in a rested state (n = 33 participants) at three testing points (n = 71 data points) to compare ocular measures to a gold standard measure of drowsiness (OSLER). The utility of these parameters for detecting drowsiness-related errors was evaluated using receiver operating characteristic curves (ROC) (adjusted by clustering for participant) and identification of optimal cutoff levels for identifying frequent drowsiness-related errors (4 missed signals in a minute using OSLER). Their accuracy was tested for detecting increasing frequencies of behavioral lapses on a different task (psychomotor vigilance task [PVT]). RESULTS: Ocular variables which measured the average duration of eyelid closure (inter-event duration [IED]) and the ratio of the amplitude to velocity of eyelid closure were reliable indicators of frequent errors (area under the curve for ROC of 0.73 to 0.83, p < 0.05). IED produced a sensitivity and specificity of 71% and 88% for detecting ≥ 3 lapses (PVT) in a minute and 100% and 86% for ≥ 5 lapses. A composite measure of several eye movement characteristics (Johns Drowsiness Scale) provided sensitivities of 77% and 100% for detecting 3 and ≥ 5 lapses in a minute, with specificities of 85% and 83%, respectively. CONCLUSIONS: Ocular measures, particularly those measuring the average duration of episodes of eye closure are promising real-time indicators of drowsiness.