Driver Performance in the Moments Surrounding a Microsleep

The role of driver head pose dynamics and instantaneous driving in safety critical events: Application of computer vision in naturalistic driving

This paper investigates the role of driver behavior especially head pose dynamics in safety-critical events (SCEs). Using a large dataset collected in a naturalistic driving study, this paper analyzes the head pose dynamics and driving behavior in moments leading up to crashes or near-crashes. The study uses advanced computer vision and mixed logit modeling techniques to identify patterns and relationships between drivers' head pose dynamics and crash involvement. The results suggest that driver-head pose dynamics, especially poses that indicate distraction and movement volatility, are important factors that can contribute to undesirable safety outcomes. Marginal effects show that angular deviation for head pose dynamics indicated by yaw, pitch and roll increase the likelihood of crash intensity by 4.56%, 4.92% and 8.26% respectively. Furthermore, traffic flow and lane changing also contribute to increase in likelihood of crash intensity. These findings provide new insights into pre-crash factors, especially human factors and safety-critical events. The study highlights the importance of considering human factors in designing driver assistance systems and developing safer vehicles. This research contributes by examining naturalistic driving data at the microscopic level with early detection of behaviors that lead to SCEs and provides a basis for future research on automation.

Revisiting the maintenance of wakefulness test: from intra-/inter-scorer agreement to normative values in patients treated for obstructive sleep apnea

The Maintenance of Wakefulness Test is widely used to objectively assess sleepiness and make safety-related decisions, but its interpretation is subjective and normative values remain debated. Our work aimed to determine normative thresholds in non-subjectively sleepy patients with well-treated obstructive sleep apnea, and to assess intra- and inter-scorer variability. We included maintenance of wakefulness tests of 141 consecutive patients with treated obstructive sleep apnea (90% men, mean (SD) age 47.5 (9.2) years, mean (SD) pre-treatment apnea-hypopnea index of 43.8 (20.3) events/h). Sleep onset latencies were independently scored by two experts. Discordant scorings were reviewed to reach a consensus and half of the cohort was double-scored by each scorer. Intra- and inter-scorer variability was assessed using Cohen's kappa for 40, 33, and 19 min mean sleep latency thresholds. Consensual mean sleep latencies were compared between four groups according to subjective sleepiness (Epworth Sleepiness Scale score < versus ≥11) and residual apnea-hypopnea index (< versus ≥15 events/h). In well-treated non-sleepy patients (n = 76), the consensual mean (SD) sleep latency was 38.4 (4.2) min (lower normal limit [mean - 2SD] = 30 min), and 80% of them did not fall asleep. Intra-scorer agreement on mean sleep latency was high but inter-scorer was only fair (Cohen's kappa 0.54 for 33-min threshold, 0.27 for 19-min threshold), resulting in changes in latency category in 4%-12% of patients. A higher sleepiness score but not the residual apnea-hypopnea index was significantly associated with a lower mean sleep latency. Our findings suggest a higher than usually accepted normative threshold (30 min) in this context and emphasise the need for more reproducible scoring approaches.

Association of Visual-Based Signals with Electroencephalography Patterns in Enhancing the Drowsiness Detection in Drivers with Obstructive Sleep Apnea

Individuals with obstructive sleep apnea (OSA) face increased accident risks due to excessive daytime sleepiness. PERCLOS, a recognized drowsiness detection method, encounters challenges from image quality, eyewear interference, and lighting variations, impacting its performance, and requiring validation through physiological signals. We propose visual-based scoring using adaptive thresholding for eye aspect ratio with OpenCV for face detection and Dlib for eye detection from video recordings. This technique identified 453 drowsiness (PERCLOS ≥ 0.3 || CLOSDUR ≥ 2 s) and 474 wakefulness episodes (PERCLOS < 0.3 and CLOSDUR < 2 s) among fifty OSA drivers in a 50 min driving simulation while wearing six-channel EEG electrodes. Applying discrete wavelet transform, we derived ten EEG features, correlated them with visual-based episodes using various criteria, and assessed the sensitivity of brain regions and individual EEG channels. Among these features, theta-alpha-ratio exhibited robust mapping (94.7%) with visual-based scoring, followed by delta-alpha-ratio (87.2%) and delta-theta-ratio (86.7%). Frontal area (86.4%) and channel F4 (75.4%) aligned most episodes with theta-alpha-ratio, while frontal, and occipital regions, particularly channels F4 and O2, displayed superior alignment across multiple features. Adding frontal or occipital channels could correlate all episodes with EEG patterns, reducing hardware needs. Our work could potentially enhance real-time drowsiness detection reliability and assess fitness to drive in OSA drivers.

Embracing sleep-onset complexity

Sleep is crucial for many vital functions and has been extensively studied. By contrast, the sleep-onset period (SOP), often portrayed as a mere prelude to sleep, has been largely overlooked and remains poorly characterized. Recent findings, however, have reignited interest in this transitional period and have shed light on its neural mechanisms, cognitive dynamics, and clinical implications. This review synthesizes the existing knowledge about the SOP in humans. We first examine the current definition of the SOP and its limits, and consider the dynamic and complex electrophysiological changes that accompany the descent to sleep. We then describe the interplay between internal and external processing during the wake-to-sleep transition. Finally, we discuss the putative cognitive benefits of the SOP and identify novel directions to better diagnose sleep-onset disorders.

Sleepiness and the transition from wakefulness to sleep

The transition from wakefulness to sleep is a progressive process that is reflected in the gradual loss of responsiveness, an alteration of cognitive functions, and a drastic shift in brain dynamics. These changes do not occur all at once. The sleep onset period (SOP) refers here to this period of transition between wakefulness and sleep. For example, although transitions of brain activity at sleep onset can occur within seconds in a given brain region, these changes occur at different time points across the brain, resulting in a SOP that can last several minutes. Likewise, the transition to sleep impacts cognitive and behavioral levels in a graded and staged fashion. It is often accompanied and preceded by a sensation of drowsiness and the subjective feeling of a need for sleep, also associated with specific physiological and behavioral signatures. To better characterize fluctuations in vigilance and the SOP, a multidimensional approach is thus warranted. Such a multidimensional approach could mitigate important limitations in the current classification of sleep, leading ultimately to better diagnoses and treatments of individuals with sleep and/or vigilance disorders. These insights could also be translated in real-life settings to either facilitate sleep onset in individuals with sleep difficulties or, on the contrary, prevent or control inappropriate sleep onsets.

Driving fatigue increases after the Spring transition to Daylight Saving Time in young male drivers: A pilot study

The Spring transition to Daylight Saving Time (DST) has been associated with several health and road safety issues. Previous literature has focused primarily on the analysis of historical crash and hospitalization data, without investigating specific crash contributing factors, such as driving fatigue. The present study aims to uncover the effects of DST-related circadian desynchrony and sleep deprivation on driving fatigue, by means of a driving simulator experiment. Eighteen participants (all males, age range 21-30 years, mean = 24.2, SD = 2.9) completed two 50-minute trials (at one week distance, same time and same day of the week) on a monotonous highway environment, the second one taking place in the week after the Spring transition to DST. Driving fatigue was evaluated by analysing several different variables (including driving-based, physiological and subjective indices) and by comparison with a historical cohort of pertinent, matched controls who had also undergone two trials, but in the absence of any time change in between. Results showed a considerable rise in fatigue levels throughout the driving task in both trials, but with significantly poorer performance in the post-DST trial, documented by a worsening in vehicle lateral control and an increase in eyelid closure. However, participants seemed unable to perceive this decrease in their alertness, which most likely prevented them from implementing fatigue-coping strategies. These findings indicate that DST has a detrimental effect on driving fatigue in young male drivers in the week after the Spring transition, and provide valuable insights into the complex relationship between DST and road safety.

Evaluation of hypersomnolence: From symptoms to diagnosis, a multidimensional approach

Hypersomnolence is a major public health issue given its high frequency, its impact on academic/occupational functioning and on accidentology, as well as its heavy socio-economic burden. The positive and aetiological diagnosis is crucial, as it determines the therapeutic strategy. It must consider the following aspects: i) hypersomnolence is a complex concept referring to symptoms as varied as excessive daytime sleepiness, excessive need for sleep, sleep inertia, or drowsiness, all of which warrant specific dedicated investigations; ii) the boundary between physiological and abnormal hypersomnolence is blurred, since most symptoms can be encountered in the general population to varying degrees without being considered as pathological, meaning that their severity, frequency, context of occurrence and related impairment need to be carefully assessed; iii) investigation of hypersomnolence relies on scales/questionnaires as well as behavioural and neurophysiological tests, which measure one or more dimensions, keeping in mind the possible discrepancy between objective and subjective assessment; iv) aetiological reasoning is driven by knowledge of the main sleep regulation mechanisms, epidemiology, and associated symptoms. The need to assess hypersomnolence is growing, both for its management, and for assessing the efficacy of treatments. The landscape of tools available for investigating hypersomnolence is constantly evolving, in parallel with research into sleep physiology and technical advances. These investigations face the challenges of reconciling subjective perception and objective data, making tools accessible to as many people as possible and predicting the risk of accidents.

Driving impairment and altered ocular activity under the effects of alprazolam and alcohol: A randomized, double-blind, placebo-controlled study

BACKGROUND

Alprazolam, also known by trade-name Xanax, is regularly detected along with alcohol in blood samples of drivers injured or killed in traffic collisions. While their co-consumption is principally legal, policy guidelines concerning fitness-to-drive are lacking and methods to index impairment are underdeveloped.

METHODS

In this randomized, double-blind, placebo-controlled, crossover trial, we examined whether legally permissible levels of alcohol [target 0.04% blood alcohol concentration (BAC)], alprazolam (1mg), and their combination impacts driving performance, and whether driving impairment can be indexed by ocular activity. Participants completed a test battery consisting of a 40-minute simulated highway drive with ocular parameters assessed simultaneously, the Karolinska Sleepiness Scale, and a confidence to drive assessment following four separate treatment combinations. The predictive efficacy of ocular parameters to identify alcohol and alprazolam-related driving impairment was also examined.

RESULTS

Among 21 healthy, fully licensed drivers (37% female, mean age 28.43, SD ± 3.96), driving performance was significantly impacted by alprazolam, alcohol, and their combination. Linear regression models revealed that the odds of an out-of-lane event occurring increased five-fold under the influence alprazolam alone and when combined with alcohol. An increase in gaze transition entropy (GTE) demonstrated the strongest association with the odds of an out-of-lane event occurring in the same minute, with both microsleeps and fixation rate achieving moderate accuracy across treatments.

CONCLUSIONS

Alprazolam and alcohol, alone and in combination, impaired select aspects of vehicle control over time. GTE, microsleeps, and fixation rate show potential as real-time indicators of driving impairment and crash risk associated with alcohol and alprazolam consumption.

Evaluation of Single-Trial Classification to Control a Visual ERP-BCI under a Situation Awareness Scenario

An event-related potential (ERP)-based brain-computer interface (BCI) can be used to monitor a user's cognitive state during a surveillance task in a situational awareness context. The present study explores the use of an ERP-BCI for detecting new planes in an air traffic controller (ATC). Two experiments were conducted to evaluate the impact of different visual factors on target detection. Experiment 1 validated the type of stimulus used and the effect of not knowing its appearance location in an ERP-BCI scenario. Experiment 2 evaluated the effect of the size of the target stimulus appearance area and the stimulus salience in an ATC scenario. The main results demonstrate that the size of the plane appearance area had a negative impact on the detection performance and on the amplitude of the P300 component. Future studies should address this issue to improve the performance of an ATC in stimulus detection using an ERP-BCI.

[Correlation of the Karolinska sleepiness scale with performance variables of the monotonous bimanual psychomotor test]

OBJECTIVE

To assess the objectivity of measuring the level of sleepiness in the subjects using a monotonous psychomotor bimanual tapping test developed by us, performed on mobile devices running Android OS.

MATERIAL AND METHODS

Four hundred and ninety-four hour-long experiments with the performance of a psychomotor test were conducted on 102 students. Using the method of mixed linear models, correlations between the levels of sleepiness according to the Karolinska Sleepiness Scale (KSS) and the Epworth Sleepiness Scale (ESS) and the behavioral indicators of the test were evaluated.

RESULTS

Statistically significant correlations between the increase in KSS scores and such indicators as a decrease in the total number of button taps and an increase in the frequency of «microsleep» episodes are shown. Statistically significant correlations of ESS score characteristics with the behavioral indicators of the test were not found.

CONCLUSION

A large statistical material shows a reliable correlation of the parameters of the psychomotor test with the level of sleepiness on the Karolinska scale, which allows using the mobile application developed by us to determine the current level of sleepiness /alertness in the field.

Acute sleep loss increases CNS health biomarkers and compromises the ability to stay awake in a sex-and weight-specific manner

Night shift work impairs vigilance performance, reduces the ability to stay awake, and compromises brain health. To investigate if the magnitude of these adverse night shift work effects differs between sexes and weight groups, 47 men and women with either normal weight or obesity participated in one night of sleep and one night of total sleep loss. During the night of sleep loss, participants' subjective sleepiness, vigilance performance, and ability to stay awake during 2-min quiet wake with eyes closed were repeatedly assessed. In addition, blood was collected in the morning after sleep loss and sleep to measure central nervous system (CNS) health biomarkers. Our analysis showed that women were sleepier during the night of sleep loss (P < 0.05) and spent more time in microsleep during quiet wake testing (P < 0.05). Finally, higher blood levels of neurofilament light chain, a biomarker of axonal damage, were found among women in the morning after sleep loss (P < 0.002). Compared with normal-weight subjects, those with obesity were more prone to fall asleep during quiet wake (P < 0.05) and exhibited higher blood levels of the CNS health biomarker pTau181 following sleep loss (P = 0.001). Finally, no differences in vigilance performance were noted between the sex and weight groups. Our findings suggest that the ability to stay awake during and the CNS health biomarker response to night shift work may differ between sexes and weight groups. Follow-up studies must confirm our findings under more long-term night shift work conditions.

The Origins of Passive, Active, and Sleep-Related Fatigue

Driving is a safety-critical task that requires an alert and vigilant driver. Most research on the topic of vigilance has focused on its proximate causes, namely low arousal and resource expenditure. The present article aims to build upon previous work by discussing the ultimate causes, or the processes that tend to precede low arousal and resource expenditure. The authors review different aspects of fatigue that contribute to a loss of vigilance and how they tend to occur; specifically, the neurochemistry of passive fatigue, the electrophysiology of active fatigue, and the chronobiology of sleep-related fatigue.

[Speech and behavioral contaminations as non-epileptic automatic behavior in Parkinson's disease]

Parkinson's disease is characterized by a variety of motor and non-motor symptoms. More than two hundred years have passed since its description, but we still discover its new manifestations. Abnormal behaviors include impulse control disorders, dopamine dysregulation syndrome, psychotic disorders and others. However, two new phenomena have been recently described in patients with PD. It can manifest in the form of doing inappropriate actions which patient doesn't recognize, or pronouncing/writing unsuitable words and phrases. Patients can't remember such episodes, but find «signs» of their unconscious activity or hear about it from attestors. This article represents a review of literature on unrelated communication interlude and automatic behavior in Parkinson's disease and discusses its possible reasons.

CE: Nurses Are More Exhausted Than Ever: What Should We Do About It?

ABSTRACT

For nurses, the challenges posed by demanding work environments and schedules often lead to fatigue, and this can be exacerbated during crises like the COVID-19 pandemic. In this article, the authors discuss causes and challenges of nurse fatigue and consider several evidence-based strategies and solutions for individual nurses and organizations. Barriers to implementation, including a negative workplace culture and inadequate staffing, are also described, and several resources are presented.

European NCAP Program Developments to Address Driver Distraction, Drowsiness and Sudden Sickness

Driver distraction and drowsiness remain significant contributors to death and serious injury on our roads and are long standing issues in road safety strategies around the world. With developments in automotive technology, including driver monitoring, there are now more options available for automotive manufactures to mitigate risks associated with driver state. Such developments in Occupant Status Monitoring (OSM) are being incorporated into the European New Car Assessment Programme (Euro NCAP) Safety Assist protocols. The requirements for OSM technologies are discussed along two dimensions: detection difficulty and behavioral complexity. More capable solutions will be able to provide higher levels of system availability, being the proportion of time a system could provide protection to the driver, and will be able to capture a greater proportion of complex real-word driver behavior. The testing approach could initially propose testing using both a dossier of evidence provided by the Original Equipment Manufacturer (OEM) alongside selected use of track testing. More capable systems will not rely only on warning strategies but will also include intervention strategies when a driver is not attentive. The roadmap for future OSM protocol development could consider a range of known and emerging safety risks including driving while intoxicated by alcohol or drugs, cognitive distraction, and the driver engagement requirements for supervision and take-over performance with assisted and automated driving features.

RoWDI: rolling window detection of sleep intrusions in the awake brain using fMRI

Objective.Brief episodes of sleep can intrude into the awake human brain due to lack of sleep or fatigue-compromising the safety of critical daily tasks (i.e. driving). These intrusions can also introduce artefactual activity within functional magnetic resonance imaging (fMRI) experiments, prompting the need for an objective and effective method of removing them.Approach.We have developed a method to track sleep-like events in awake humans via rolling window detection of intrusions (RoWDI) of fMRI signal template. These events can then be used in voxel-wise event-related analysis of fMRI data. To test this approach, we generated a template of fMRI activity associated with transition to sleep via simultaneous fMRI and electroencephalogram (EEG) (N= 10). RoWDI was then used to identify sleep-like events in 20 individuals performing a cognitive task during fMRI after a night of partial sleep deprivation. This approach was further validated in an independent fMRI dataset (N= 56).Main results.Our method (RoWDI) was able to infer frequent sleep-like events during the cognitive task performed after sleep deprivation. The sleep-like events were associated with on average of 20% reduction in pupil size and prolonged response time. The blood-oxygen-level-dependent activity during the sleep-like events covered thalami-cortical regions, which although spatially distinct, co-existed with, task-related activity. These key findings were validated in the independent dataset.Significance.RoWDI can reliably detect spontaneous sleep-like events in the human brain. Thus, it may also be used as a tool to delineate and account for neural activity associated with wake-sleep transitions in both resting-state and task-related fMRI studies.

I think I'm sleepy, therefore I am - Awareness of sleepiness while driving: A systematic review

Driver drowsiness contributes to 10-20% of motor vehicle crashes. To reduce crash risk, ideally drivers would be aware of the drowsy state and cease driving. The extent to which drivers can accurately identify sleepiness remains under much debate. We systematically examined whether individuals are aware of sleepiness while driving, and whether this accurately reflects driving impairment, using meta-analyses and narrative review. Within this scope, there is high variability in measures of subjective sleepiness, driving performance and physiologically-derived drowsiness, and statistical analyses. Thirty-four simulated/naturalistic driving studies were reviewed. To summarise, drivers were aware of sleepiness, and this was associated to physiological drowsiness and driving impairment, such that high levels of sleepiness significantly predicted crash events and lane deviations. Subjective sleepiness was more strongly correlated (i) with physiological drowsiness compared to driving outcomes; (ii) under simulated driving conditions compared to naturalistic drives; and (iii) when examined using the Karolinska sleepiness scale (KSS) compared to other measures. Gaps remain in relation to how age, sex, and varying degrees of sleep loss may influence this association. This review provides evidence that drivers are aware of drowsiness while driving, and stopping driving when feeling 'sleepy' may significantly reduce crash risk.

Microsleep assessment enhances interpretation of the Maintenance of Wakefulness Test

STUDY OBJECTIVES

The Maintenance of Wakefulness Test (MWT) is used to objectively evaluate an individual's ability to remain awake; however, microsleeps are not included in the assessment. We aimed to determine if microsleep data prior to sleep onset assisted in interpretation of ability to maintain wakefulness across a range of typical patient groups.

METHODS

Forty-eight patients referred for overnight polysomnography and subsequent MWT were included. Patients were divided into 3 groups (treated obstructive sleep apnea [OSA], untreated OSA, or treated idiopathic hypersomnia or narcolepsy) based on prior medical diagnosis. Demographics, clinical characteristics, polysomnography, and MWT variables, including frequency, distribution, duration, and latency of microsleeps were compared between groups.

RESULTS

Microsleeps were observed in MWT trials significantly more frequently in patients with treated idiopathic hypersomnia/narcolepsy over the course of the day (0.34 ± 0.06 vs 0.07 ± 0.02 microsleeps/min; P < .001) and in patients with untreated OSA toward the end of the day (0.31 ± 0.06 vs 0.05 ± 0.02 microsleeps/min; P < .001) compared to the group with treated OSA. Microsleeps were often observed in series and earlier in patients with treated idiopathic hypersomnia/narcolepsy (10.9 ± 1.6 minutes) and those with untreated OSA (16.2 ± 2.7 minutes) compared to the group with treated OSA (24.9 ± 3.0 minutes; P < .05), and, if taken into consideration, would increase the proportion of patients demonstrating inability to maintain wakefulness by 33% and 22%, respectively.

CONCLUSIONS

MWT performance varies significantly across patient groups. Microsleep analysis prior to sleep onset may be a more sensitive measure of patient daytime wakefulness than sleep latency alone and should be considered in MWT assessment.

CITATION

Anniss AM, Young A, O'Driscoll DM. Microsleep assessment enhances interpretation of the Maintenance of Wakefulness Test. J Clin Sleep Med. 2021;17(8):1571-1578.

Sleepiness Behind the Wheel and the Implementation of European Driving Regulations

Sleep disturbance and sleepiness are established risk factors for driving accidents and obstructive sleep apnea (OSA) is the most prevalent medical disorder associated with excessive daytime sleepiness. Because effective treatment of OSA reduces accident risk, several jurisdictions have implemented regulations concerning the ability of patients with OSA to drive, unless effectively treated. This review provides a practical guide for clinicians who may be requested to certify a patient with OSA as fit to drive regarding the scope of the problem, the role of questionnaires and driving simulators to evaluate sleepiness, and the benefit of treatment on accident risk.

Sleep-deprived car-following: Indicators of rear-end crash potential

Safety assessment among sleep-deprived drivers is a challenging research area with only a few sleep-related studies investigating safety performance during car-following. Therefore, this study aimed to measure the effects of partial sleep deprivation on driver safety during car-following. Fifty healthy male drivers with no prior history of any sleep-related disorders, drove the driving simulator in three conditions of varying sleep duration: a baseline (no sleep deprivation), test session (TS1) after one night of PSD (sleep ≤4.5 h/night) and TS2 after two consecutive nights of PSD. The reduced sleep in PSD sessions was monitored using an Actiwatch. Karolinska Sleepiness Scale was used to indicate loss of alertness among drivers. Each drive included a car-following task to measure longitudinal safety indicators based on speed and headway management: normalized time exposed to critical gap (TECG'), safety critical time headway and speed variability with respect to leading vehicle's speed (SPV). Crash potential index (CPI) was also determined from deceleration rate of drivers during car-following and was found correlated with other indicators. Therefore, to determine the aggregate influence of PSD on safety during car-following, CPI was modelled in terms of TECG, SPV, THW and other covariates. All safety metrics were modelled using generalized mixed effects regression models. The results showed that compared to the baseline drive, critical time headway decreased by 0.65 and 1.08 times whereas speed variability increased by 1.34 and 1.28 times during the TS1 and TS2, respectively, both indicating higher crash risk. However, decrease in TECG' by 64 % and 56 % during TS1 and TS2, respectively indicate compensatory measures to avoid risks due to sleep loss. A fractional regression model of crash potential revealed that low time-headway and higher speed variability and high time exposed to critical gap (TECG') significantly contribute to higher CPI values indicating higher safety risk. Other covariates such as sleep duration, professional driving experience and history of traffic violations were also associated with safety indicators and CPI, however no significant effects of age were noticed in the study. The study findings present the safety indicators sensitive to rear-end crashes specifically under PSD conditions, which can be used in designing collisions avoidance systems and strategies to improve overall traffic safety.

Microsleep versus Sleep Onset Latency during Maintenance Wakefulness Tests: Which One Is the Best Marker of Sleepiness?

The interpretation of the Maintenance Wakefulness Test (MWT) relies on sleep onset detection. However, microsleeps (MSs), i.e., brief periods of sleep intrusion during wakefulness, may occur before sleep onset. We assessed the prevalence of MSs during the MWT and their contribution to the diagnosis of residual sleepiness in patients treated for obstructive sleep apnea (OSA) or hypersomnia. The MWT of 98 patients (89 OSA, 82.6% male) were analyzed for MS scoring. Polysomnography parameters and clinical data were collected. The diagnostic value for detecting sleepiness (Epworth Sleepiness Scale > 10) of sleep onset latency (SOL) and of the first MS latency (MSL) was assessed by the area under the receiver operating characteristic (ROC) curve (AUC, 95% CI). At least one MS was observed in 62.2% of patients. MSL was positively correlated with SOL (r = 0.72, p < 0.0001) but not with subjective scales, clinical variables, or polysomnography parameters. The use of SOL or MSL did not influence the diagnostic performance of the MWT for subjective sleepiness assessment (AUC = 0.66 95% CI (0.56, 0.77) versus 0.63 95% CI (0.51, 0.74)). MSs are frequent during MWTs performed in patients treated for sleep disorders, even in the absence of subjective sleepiness, and may represent physiological markers of the wake-to-sleep transition.

The impact of the wake maintenance zone on attentional capacity, physiological drowsiness, and subjective task demands during sleep deprivation

We aimed to investigate the impact of the Wake Maintenance Zone (WMZ) on measures of drowsiness, attention, and subjective performance under rested and sleep deprived conditions. We studied 23 healthy young adults (18 males; mean age = 25.41 ± 5.73 years) during 40 hr of total sleep deprivation under constant routine conditions. Participants completed assessments of physiological drowsiness (EEG-scored slow eye movements and microsleeps), sustained attention (PVT), and subjective task demands every two hours, and four-hourly ocular motor assessment of inhibitory control (inhibition of reflexive saccades on an anti-saccade task). Tests were analyzed relative to dim light melatonin onset (DLMO); the WMZ was defined as the 3 hr prior to DLMO, and the preceding 3 hr window was deemed the pre-WMZ. The WMZ did not mitigate the adverse impact of ~37 hr sleep deprivation on drowsiness, sustained attention, response inhibition, and self-rated concentration and difficulty, relative to rested WMZ performance (~13 hr of wakefulness). Compared to the pre-WMZ, though, the WMZ improved measures of sustained attention, and subjective concentration and task difficulty, during sleep deprivation. Cumulatively, these results expand on previous work by characterizing the beneficial effects of the WMZ on operationally-relevant indices of drowsiness, inhibitory attention control, and self-rated concentration and task difficulty relative to the pre-WMZ during sleep deprivation. These results may inform scheduling safety-critical tasks at more optimal circadian times to improve workplace performance and safety.

Sleep inertia in automated driving: Post-sleep take-over and driving performance

Sleep is emerging as a new driver state in automated driving. Post-sleep performance impairments due to sleep inertia, the transitional phase from sleep to wakefulness that can take up to 30 min, are a potential safety issue. Take-over performance immediately after sleep is impaired and drivers perceive the take-over as critical. The aim of the presented study was to assess take-over behavior immediately after sleep and driving behavior during the 10 min after sleep. A study with N = 31 drivers was conducted in a high-fidelity driving simulator. Take-over performance and driving performance were assessed a) under alert baseline conditions and b) after awakening from electroencephalography-confirmed stable sleep. Take-over performance 15 s after awakening was impaired resulting in more driving errors compared to the alert baseline. Lane keeping was dramatically impaired in the first 3 min after sleep and recovered rapidly. Drivers drove slower after sleep and speed keeping was less stable for at least 10 min. The results suggest that human-machine interaction design should account for the drivers' impaired post-sleep driving performance.

Effects of advanced warning information systems on secondary crash risk under connected vehicle environment

This study evaluated the impact of an optimal in-vehicle advanced warning information service in a connected vehicle (CV) environment to prevent secondary crashes. Driving simulation experiments were designed and performed to analyze driving behavior. The forward crash situation was reproduced in a simulated highway environment, and the safety effects were assessed based on simulation data from a driving simulator (DS). To explore and analyze the effectiveness of crash notifications from the advanced warning information system (AWIS) for preventing secondary crashes, this study utilized repeated measures of multivariate analysis of variance (MANOVA), repeated measures of ANOVA, paired t-test, and Wilcoxon signed rank test. The results from this paper indicate that a warning information system was effective to prevent secondary crash risks, in general.

European Respiratory Society statement on sleep apnoea, sleepiness and driving risk

Obstructive sleep apnoea (OSA) is highly prevalent and is a recognised risk factor for motor vehicle accidents (MVA). Effective treatment with continuous positive airway pressure has been associated with a normalisation of this increased accident risk. Thus, many jurisdictions have introduced regulations restricting the ability of OSA patients from driving until effectively treated. However, uncertainty prevails regarding the relative importance of OSA severity determined by the apnoea–hypopnoea frequency per hour and the degree of sleepiness in determining accident risk. Furthermore, the identification of subjects at risk of OSA and/or accident risk remains elusive. The introduction of official European regulations regarding fitness to drive prompted the European Respiratory Society to establish a task force to address the topic of sleep apnoea, sleepiness and driving with a view to providing an overview to clinicians involved in treating patients with the disorder. The present report evaluates the epidemiology of MVA in patients with OSA; the mechanisms involved in this association; the role of screening questionnaires, driving simulators and other techniques to evaluate sleepiness and/or impaired vigilance; the impact of treatment on MVA risk in affected drivers; and highlights the evidence gaps regarding the identification of OSA patients at risk of MVA.

Automatic detection of microsleep episodes with feature-based machine learning

STUDY OBJECTIVES

Microsleep episodes (MSEs) are brief episodes of sleep, mostly defined to be shorter than 15 s. In the electroencephalogram (EEG), MSEs are mainly characterized by a slowing in frequency. The identification of early signs of sleepiness and sleep (e.g. MSEs) is of considerable clinical and practical relevance. Under laboratory conditions, the maintenance of wakefulness test (MWT) is often used for assessing vigilance.

METHODS

We analyzed MWT recordings of 76 patients referred to the Sleep-Wake-Epilepsy-Center. MSEs were scored by experts defined by the occurrence of theta dominance on ≥1 occipital derivation lasting 1-15 s, whereas the eyes were at least 80% closed. We calculated spectrograms using an autoregressive model of order 16 of 1 s epochs moved in 200 ms steps in order to visualize oscillatory activity and derived seven features per derivation: power in delta, theta, alpha and beta bands, ratio theta/(alpha + beta), quantified eye movements, and median frequency. Three algorithms were used for MSE classification: support vector machine (SVM), random forest (RF), and an artificial neural network (long short-term memory [LSTM] network). Data of 53 patients were used for the training of the classifiers, and 23 for testing.

RESULTS

MSEs were identified with a high performance (sensitivity, specificity, precision, accuracy, and Cohen's kappa coefficient). Training revealed that delta power and the ratio theta/(alpha + beta) were most relevant features for the RF classifier and eye movements for the LSTM network.

CONCLUSIONS

The automatic detection of MSEs was successful for our EEG-based definition of MSEs, with good performance of all algorithms applied.

A pre-drive ocular assessment predicts alertness and driving impairment: A naturalistic driving study in shift workers

Sleepiness is a major contributor to motor vehicle crashes and shift workers are particularly vulnerable. There is currently no validated objective field-based measure of sleep-related impairment prior to driving. Ocular parameters are promising markers of continuous driver alertness in laboratory and track studies, however their ability to determine fitness-to-drive in naturalistic driving is unknown. This study assessed the efficacy of a pre-drive ocular assessment for predicting sleep-related impairment in naturalistic driving, in rotating shift workers. Fifteen healthcare workers drove an instrumented vehicle for 2 weeks, while working a combination of day, evening and night shifts. The vehicle monitored lane departures and behavioural microsleeps (blinks >500 ms) during the drive. Immediately prior to driving, ocular parameters were assessed with a 4-min test. Lane departures and behavioural microsleeps occurred on 17.5 % and 10 % of drives that had pre-drive assessments, respectively. Pre-drive blink duration significantly predicted behavioural microsleeps and showed promise for predicting lane departures (AUC = 0.79 and 0.74). Pre-drive percentage of time with eyes closed had high accuracy for predicting lane departures and behavioural microsleeps (AUC = 0.73 and 0.96), although was not statistically significant. Pre-drive psychomotor vigilance task variables were not statistically significant predictors of lane departures. Self-reported sleep-related and hazardous driving events were significantly predicted by mean blink duration (AUC = 0.65 and 0.69). Measurement of ocular parameters pre-drive predict drowsy driving during naturalistic driving, demonstrating potential for fitness-to-drive assessment in operational environments.

The effects of different fatigue levels on brain-behavior relationships in driving

BACKGROUND

In the past decade, fatigue has been regarded as one of the main factors impairing task performance and increasing behavioral lapses during driving, even leading to fatal car crashes. Although previous studies have explored the impact of acute fatigue through electroencephalography (EEG) signals, it is still unclear how different fatigue levels affect brain-behavior relationships.

METHODS

A longitudinal study was performed to investigate the brain dynamics and behavioral changes in individuals under different fatigue levels by a sustained attention task. This study used questionnaires in combination with actigraphy, a noninvasive means of monitoring human physiological activity cycles, to conduct longitudinal assessment and tracking of the objective and subjective fatigue levels of recruited participants. In this study, degrees of effectiveness score (fatigue rating) are divided into three levels (normal, reduced, and high risk) by the SAFTE fatigue model.

RESULTS

Results showed that those objective and subjective indicators were negatively correlated to behavioral performance. In addition, increased response times were accompanied by increased alpha and theta power in most brain regions, especially the posterior regions. In particular, the theta and alpha power dramatically increased in the high-fatigue (high-risk) group. Additionally, the alpha power of the occipital regions showed an inverted U-shaped change.

CONCLUSION

Our results help to explain the inconsistent findings among existing studies, which considered the effects of only acute fatigue on driving performance while ignoring different levels of resident fatigue, and potentially lead to practical and precise biomathematical models to better predict the performance of human operators.

Exploring microscopic driving volatility in naturalistic driving environment prior to involvement in safety critical events-Concept of event-based driving volatility

The sequence of instantaneous driving decisions and its variations, known as driving volatility, prior to involvement in safety critical events can be a leading indicator of safety. This study focuses on the component of "driving volatility matrix" related to specific normal and safety-critical events, named "event-based volatility." The research issue is characterizing volatility in instantaneous driving decisions in the longitudinal and lateral directions, and how it varies across drivers involved in normal driving, crash, and/or near-crash events. To explore the issue, a rigorous quasi-experimental study design is adopted to help compare driving behaviors in normal vs unsafe outcomes. Using a unique real-world naturalistic driving database from the 2^nd Strategic Highway Research Program (SHRP), a test set of 9593 driving events featuring 2.2 million temporal samples of real-world driving are analyzed. This study features a plethora of kinematic sensors, video, and radar spatiotemporal data about vehicle movement and therefore offers the opportunity to initiate such exploration. By using information related to longitudinal and lateral accelerations and vehicular jerk, 24 different aggregate and segmented measures of driving volatility are proposed that captures variations in extreme instantaneous driving decisions. In doing so, careful attention is given to the issue of intentional vs. unintentional volatility. The volatility indices, as leading indicators of near-crash and crash events, are then linked with safety critical events, crash propensity, and other event specific explanatory variables. Owing to the presence of unobserved heterogeneity and omitted variable bias, fixed- and random-parameter discrete choice models are developed that relate crash propensity to unintentional driving volatility and other factors. Statistically significant evidence is found that driver volatilities in near-crash and crash events are significantly greater than volatility in normal driving events. After controlling for traffic, roadway, and unobserved factors, the results suggest that greater intentional volatility increases the likelihood of both crash and near-crash events. A one-unit increase in intentional volatility is associated with positive vehicular jerk in longitudinal direction increases the chance of crash and near-crash outcome by 15.79 and 12.52 percentage points, respectively. Importantly, intentional volatility in positive vehicular jerk in lateral direction has more negative consequences than intentional volatility in positive vehicular jerk in longitudinal direction. Compared to acceleration/deceleration, vehicular jerk can better characterize the volatility in microscopic instantaneous driving decisions prior to involvement in safety critical events. Finally, the magnitudes of correlations exhibit significant heterogeneity, and that accounting for the heterogeneous effects in the modeling framework can provide more reliable and accurate results. The study demonstrates the value of quasi-experimental study design and big data analytics for understanding extreme driving behaviors in safe vs. unsafe driving outcomes.

Assessment of Sleepiness in Drivers: Current Methodology and Future Possibilities

Many patients with obstructive sleep apnea syndrome (OSAS) drive a vehicle both for pleasure and as part of their employment. Some, but not all, patients with OSAS are at increased risk of being involved in road traffic accidents. Clinicians are often asked to make recommendations about an individual's fitness to drive, and these are likely to be inconsistent in the absence of objective criteria. This article discusses the current practice of the assessment of individuals' sleepiness with respect to driving, the limitations of available techniques, and future possibilities.

Sleepiness as a Local Phenomenon

Sleep occupies a third of our life and is a primary need for all animal species studied so far. Nonetheless, chronic sleep restriction is a growing source of morbidity and mortality in both developed and developing countries. Sleep loss is associated with the subjective feeling of sleepiness and with decreased performance, as well as with detrimental effects on general health, cognition, and emotions. The ideas that small brain areas can be asleep while the rest of the brain is awake and that local sleep may account for at least some of the cognitive and behavioral manifestations of sleepiness are making their way into the scientific community. We herein clarify the different ways sleep can intrude into wakefulness, summarize recent scientific advances in the field, and offer some hypotheses that help framing sleepiness as a local phenomenon.

Microsleep episodes in the borderland between wakefulness and sleep

Study objectives

The wake-sleep transition zone represents a poorly defined borderland, containing, for example, microsleep episodes (MSEs), which are of potential relevance for diagnosis and may have consequences while driving. Yet, the scoring guidelines of the American Academy of Sleep Medicine (AASM) completely neglect it. We aimed to explore the borderland between wakefulness and sleep by developing the Bern continuous and high-resolution wake-sleep (BERN) criteria for visual scoring, focusing on MSEs visible in the electroencephalography (EEG), as opposed to purely behavior- or performance-defined MSEs.

Methods

Maintenance of Wakefulness Test (MWT) trials of 76 randomly selected patients were retrospectively scored according to both the AASM and the newly developed BERN scoring criteria. The visual scoring was compared with spectral analysis of the EEG. The quantitative EEG analysis enabled a reliable objectification of the visually scored MSEs. For less distinct episodes within the borderland, either ambiguous or no quantitative patterns were found.

Results

As expected, the latency to the first MSE was significantly shorter in comparison to the sleep latency, defined according to the AASM criteria. In certain cases, a large difference between the two latencies was observed and a substantial number of MSEs occurred between the first MSE and sleep. Series of MSEs were more frequent in patients with shorter sleep latencies, while isolated MSEs were more frequent in patients who did not reach sleep.

Conclusion

The BERN criteria extend the AASM criteria and represent a valuable tool for in-depth analysis of the wake-sleep transition zone, particularly important in the MWT.

Evaluation of a Road Safety Education Program Based on Driving Under Influence and Traffic Risks for Higher Secondary School Students in Belgium

Road safety education has been recognized as an instrument for reducing road accidents. This study aims to evaluate the road safety education program “Traffic Weeks” among higher secondary school students (age 16–19) in Belgium. The program focuses on driving under influence (DUI) and traffic risks. This study investigates whether the program has an effect on socio-cognitive variables using a questionnaire based on the theory of planned behavior. During the pre-test, 445 students filled in the questionnaire, while 253 students filled in the questionnaire during the post-test. Of these, 175 questionnaires could be matched. The results indicate that the students already had quite a supportive view of road safety at pre-test, with female students showing a more supportive view of road safety than male students. The DUI workshop had a positive effect on most socio-cognitive variables (attitude, subjective norm-friends, and intention) of female students in general education, while the traffic risks workshop only affected perceived behavioral control of female students. In terms of appreciation, students had a significantly higher appreciation of the DUI workshop compared to the traffic risks workshop. During the focus groups, students gave recommendations to improve the program.

Temporal patterns of driving fatigue and driving performance among male taxi drivers in Hong Kong: A driving simulator approach

This study uses a questionnaire survey and a driving simulator test to investigate the temporal patterns of variations in driving fatigue and driving performance in 50 male taxi drivers in Hong Kong. Each driver visited the laboratory three times: before, during, and after a working shift. The survey contained a demographic questionnaire and the Brief Fatigue Inventory. A following-braking simulator test session was conducted at two speeds (50 and 80 km/h) by each driver at each of his three visits, and the driver's performance in brake reaction, lane control, speed control, and steering control were recorded. A random-effects modeling approach was incorporated to address the unobserved heterogeneity caused by the repeated measures. In the results, a recovery effect and a lagging effect were defined for the driving fatigue and performance measures because their temporal patterns were concavely quadratic and had a 1-hour delay compared to the temporal patterns of occupied taxi trips and taxi crash risk in Hong Kong. Demographic variables, such as net income and driver age, also had significant effects on the measured driving fatigue and performance. Policies regarding taxi management and operation based on the modeling results are proposed to alleviate the taxi safety situation in Hong Kong and worldwide.

Bibliometric analysis of simulated driving research from 1997 to 2016

OBJECTIVE

The objective of this study was to explore the evolution footprints of simulated driving research in the past 20 years through rigorous and systematic bibliometric analysis, to provide insights regarding when and where the research was performed and by whom and how the mainstream content evolved over the years.

METHODS

The analysis began with data retrieval in Web of Science with defined search terms related to simulated driving. BibExcel and CiteSpace were employed to conduct the performance analysis and co-citation network analysis; that is, probe of the performance of institutes, journals, authors, and research hotspots.

RESULTS

A total of 3,766 documents were filtered out and presented an exponential growth from 1997 to 2016. The United States contributed the most publications as well as international collaborations followed by Germany and China. In addition, several universities in The Netherlands and the United States dominated the list of contributing institutes. The leading journals were in transportation and ergonomics. The leading researchers were also recognized among the 8,721 contributing authors, such as J. D. Lee, D. L. Fisher, J. H. Kim, and K. A. Brookhuis. Finally, the co-citation analysis illuminated the evolution of simulated driving research that covered the following topics roughly in chronological order: task-induced stress, drivers with neurological disorders, alertness and sleepiness while driving, trust toward driving assistance systems, driver distraction, the effect of drug use, the validity of simulators, and automated driving.

CONCLUSIONS

This article employed bibliometric tools to probe the contributing countries, institutes, journals, authors, and mainstream hotspots of simulated driving research in the past 20 years. A systematic bibliometric analysis of this field will help researchers realize the panorama of global simulated driving and establish future research directions.

Temporal evolution of neural activity and connectivity during microsleeps when rested and following sleep restriction

Even when it is critical to stay awake, such as when driving, sleep deprivation weakens one's ability to do so by substantially increasing the propensity for microsleeps. Microsleeps are complete lapses of consciousness but, paradoxically, are associated with transient increases in cortical activity. But do microsleeps provide a benefit in terms of attenuating the need for sleep? And is the neural response to microsleeps altered by the degree of homeostatic drive to sleep? In this study, we continuously monitored eye-video, visuomotor responsiveness, and brain activity via fMRI in 20 healthy subjects during a 20-min visuomotor tracking task following a normally-rested night and a sleep-restricted (4-h) night. As expected, sleep restriction led to an increased number of microsleeps and an increased variability in tracking error. Microsleeps exhibited transient increases in regional activity in the fronto-parietal and parahippocampal area. Network analyses revealed divergent transient changes in the right fronto-parietal, dorsal-attention, default-mode, and thalamo-cortical functional networks. In all subjects, tracking error immediately following microsleeps was improved compared to before the microsleeps. Importantly, post-microsleep recovery in tracking response speed was associated with hyperactivation in the thalamo-cortical network. The temporal evolution of functional connectivity within the frontal and posterior nodes of the default-mode network and between the right fronto-parietal and default-mode networks was associated with temporal changes in visuomotor responsiveness. These findings demonstrate distinct brain-network-level changes in brain activity during microsleeps and suggest that neural activity in the thalamo-cortical network may facilitate the transient recovery from microsleeps. The temporal pattern of evolution in brain activity and performance is indicative of dynamic changes in vigilance during the struggle to stay awake following sleep loss.

Driver education: Enhancing knowledge of sleep, fatigue and risky behaviour to improve decision making in young drivers

This study assessed the impact of an education program on knowledge of sleepiness and driving behaviour in young adult drivers and their performance and behaviour during simulated night driving. Thirty-four participants (18-26 years old) were randomized to receive either a four-week education program about sleep and driving or a control condition. A series of questionnaires were administered to assess knowledge of factors affecting sleep and driving before and after the four-week education program. Participants also completed a two hour driving simulator task at 1am after 17 h of extended wakefulness to assess the impact on driving behaviour. There was an increase in circadian rhythm knowledge in the intervention group following the education program. Self-reported risky behaviour increased in the control group with no changes in other aspects of sleep knowledge. There were no significant differences in proportion of intervention and control participants who had microsleeps (p ≤ .096), stopped driving due to sleepiness (p = .107), recorded objective episodes of drowsiness (p = .455), and crashed (p = .761), although there was a trend towards more control participants having microsleeps and stopping driving. Those in the intervention group reported higher subjective sleepiness at the end of the drive [M = 6.25, SD = 3.83, t(31) = 2.15, p = .05] and were more likely to indicate that they would stop driving [M = 3.08, SD = 1.16, t(31) = 2.24, p = .04]. The education program improved some aspects of driver knowledge about sleep and safety. The results also suggested that the education program lead to an increased awareness of sleepiness. Education about sleep and driving could reduce the risk of drowsy driving and associated road trauma in young drivers, but requires evaluation in a broader sample with assessment of real world driving outcomes.

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.

Name that tune: Mitigation of driver fatigue via a song naming game

Fatigued driving contributes to a substantial number of motor vehicle accidents each year. Music listening is often employed as a countermeasure during driving in order to mitigate the effects of fatigue. Though music listening has been established as a distractor in the sense that it increases cognitive load during driving, it is possible that increased cognitive load is desirable under particular circumstances. For instance, during situations that typically result in cognitive underload, such as driving in a low-traffic monotonous stretch of highway, it may be beneficial for cognitive load to increase, thereby necessitating allocation of greater cognitive resources to the task of driving and attenuating fatigue. In the current study, we employed a song-naming game as a countermeasure to fatigued driving in a simulated monotonous environment. During the first driving session, we established that driving performance deteriorates in the absence of an intervention following 30min of simulated driving. During the second session, we found that a song-naming game employed at the point of fatigue onset was an effective countermeasure, as reflected by simulated driving performance that met or exceeded fresh driving behavior and was significantly better relative to fatigued performance during the first driving session.

CE: Can Your Older Patients Drive Safely?

: In many areas of the world, driving is an essential part of life and for reasons of comfort, convenience, and security remains the primary mode of transportation among older adults. Both normal aging and diseases that are more prevalent in advanced age can substantially reduce older drivers' functional abilities, elevating their risk of involvement in motor vehicle accidents and serious injury or death. Identifying and intervening with older drivers at increased crash risk is an important aspect of preventive medicine. The authors discuss the specific driving risks adults face as they age and how nurses can raise older patients' awareness of these risks. They also discuss the importance of connecting older adults to community resources that may help them continue driving safely for a longer period or find alternative transportation options.

Utilization of a combined EEG/NIRS system to predict driver drowsiness

The large number of automobile accidents due to driver drowsiness is a critical concern of many countries. To solve this problem, numerous methods of countermeasure have been proposed. However, the results were unsatisfactory due to inadequate accuracy of drowsiness detection. In this study, we introduce a new approach, a combination of EEG and NIRS, to detect driver drowsiness. EEG, EOG, ECG and NIRS signals have been measured during a simulated driving task, in which subjects underwent both awake and drowsy states. The blinking rate, eye closure, heart rate, alpha and beta band power were used to identify subject's condition. Statistical tests were performed on EEG and NIRS signals to find the most informative parameters. Fisher's linear discriminant analysis method was employed to classify awake and drowsy states. Time series analysis was used to predict drowsiness. The oxy-hemoglobin concentration change and the beta band power in the frontal lobe were found to differ the most between the two states. In addition, these two parameters correspond well to an awake to drowsy state transition. A sharp increase of the oxy-hemoglobin concentration change, together with a dramatic decrease of the beta band power, happened several seconds before the first eye closure.

Prefrontal Cortex Activation and Young Driver Behaviour: A fNIRS Study

Road traffic accidents consistently show a significant over-representation for young, novice and particularly male drivers. This research examines the prefrontal cortex activation of young drivers and the changes in activation associated with manipulations of mental workload and inhibitory control. It also considers the explanation that a lack of prefrontal cortex maturation is a contributing factor to the higher accident risk in this young driver population. The prefrontal cortex is associated with a number of factors including mental workload and inhibitory control, both of which are also related to road traffic accidents. This experiment used functional near infrared spectroscopy to measure prefrontal cortex activity during five simulated driving tasks: one following task and four overtaking tasks at varying traffic densities which aimed to dissociate workload and inhibitory control. Age, experience and gender were controlled for throughout the experiment. The results showed that younger drivers had reduced prefrontal cortex activity compared to older drivers. When both mental workload and inhibitory control increased prefrontal cortex activity also increased, however when inhibitory control alone increased there were no changes in activity. Along with an increase in activity during overtaking manoeuvres, these results suggest that prefrontal cortex activation is more indicative of workload in the current task. There were no differences in the number of overtakes completed by younger and older drivers but males overtook significantly more than females. We conclude that prefrontal cortex activity is associated with the mental workload required for overtaking. We additionally suggest that the reduced activation in younger drivers may be related to a lack of prefrontal maturation which could contribute to the increased crash risk seen in this population.

End of OSLER Test Sessions in Parkinson’s Disease do not Correspond to True Sleep Onset: Results from an Exploratory Study

The aim of the present study was to evaluate the correlation between the end of an Oxford sleep resistance (OSLER) test session and a neurophysiological marker of sleep onset in Parkinson’s disease (PD) patients. Single center study was conducted in PD patients with excessive daytime sleepiness [Epworth sleepiness scale (ESS) >9]. The OSLER test was conducted with a concomitant electroencephalography (EEG), electromyography (mentalis), right and left electroculogram, and video monitoring. Neurophysiological (NP) sleep onset was defined according to AASM criteria (2005). Five PD patients with mean ESS of 14 (10–16) were included. OSLER test duration was shorter than 40 min in all patients (mean duration 20 min and 39 s). No patient fulfilled neurophysiological criteria to sleep onset at the time of OSLER test termination. In 13 OSLER sessions that ended before 40 min, eight had microsleeps in the last 30 s before the end of the test. NP monitoring showed signs of sleepiness in all patients. In PD patients, the early termination of an OSLER test session may not correspond to NP criteria of sleep onset. However, in all PD patients with abnormal OSLER results, there were EEG signs of sleepiness, which do not exclude the potential utility of OSLER test to evaluate the risk of falling asleep.

The role of expert evaluation for microsleep detection

Recently, it has been shown by overnight driving simulation studies that microsleep density is the only known sleepiness indicator which rapidly increases within a few seconds immediately before sleepiness related crashes. This indicator is based solely on EEG and EOG and subsequent adaptive pattern recognition. Accurate microsleep recognition is very important for the performance of this sleepiness indicator. The question is whether expensive evaluations of microsleep events by a) experts are necessary or b) non-experts provide sufficient evaluations. Based on 11,114 microsleep events in case a) and 12,787 in case b) recognition accuracies were investigated utilizing (i) artificial neural networks and (ii) support-vector machines. Cross validated classification accuracies ranged between 92.2 % for (i,b) and 99.3 % for (ii, a). It is concluded that expert evaluations are very important to provide independent information for detecting microsleep.