Levels Of Subjective Sleepiness Research Articles

The Role of Sleep for Age-Related Differences in Neurobehavioral Performance.

This study investigated developmental changes from childhood to adulthood in neurobehavioral performance and sleep measures. While many studies have examined age-related changes between childhood and adolescence and from mid-to-late adulthood, young adulthood has been overlooked. The main aim of this study was to investigate the effects of sleep loss on developmental changes in neurobehavioral performance and sleepiness in a natural setting. A total of 119 children, adolescents, and young adults (38 children aged 6-9; 38 adolescents aged 13-19; and 43 young adults aged 20-27) wore an actigraph for a continuous five-weekday night. Subjective sleepiness (Karolinska Sleepiness Scale) and neurobehavioral performance (using the psychomotor vigilance test and the digit symbol substitution test) were measured on five school days. The results showed that adolescents and young adults outperformed children on both the digit symbol substitution test and the psychomotor vigilance test measures. However, adolescents committed more errors of commission on the psychomotor vigilance test and reported higher levels of subjective sleepiness. The results are discussed in relation to brain maturation in various cognitive functions.

Analysis of heart rate indices at different levels of sleepiness

The objective detection of sleepiness through physiological indices is crucial for ensuring transportation and industrial safety. As gadgets become more commonplace for measuring heart rate, it is important to identify valid indices that correlate with the level of sleepiness. Research indicates that time-domain and frequency-domain heart rate indices align with levels of alertness and sleepiness [e.g., 1, 2]. The aim of this paper is to identify heart rate indices that correlate with varying degrees of evening sleepiness in vivo, whether low or high. The data analyzed in this paper was obtained from 32 recordings from the SSDD (Subjective Sleepiness Dynamics Dataset) collected at the UNN Cyberpsychology Laboratory since 2022. The experiment was designed in the following manner: participants put on a heart rhythm sensor (Polar H10) at 7:40 PM in their homes and connected it to a smartphone app. Participants then completed a self-reported questionnaire in the electronic system. Starting at 8:00 PM, and every 30 minutes thereafter, the participant recorded data on the subjective level of sleepiness via the Karolinska (KSS) and Stanford (SSS) sleepiness scales up until the time of the participant’s bedtime. The selection of 32 recordings met specific criteria: all participants went to bed between 10:30 and 11:00 PM and completed both the KSS and SSS on time at each time point (08:00, 08:30, 09:00, 09:30, and 10:00 PM). For each time point, an integral sleepiness score was calculated according to the formula: sl=(KSS/10+SSS/7)/2. The 4-minute rhythmogram recordings corresponding to the time points of KSS and SSS filling were chosen for analysis. Data were processed in Jupyter Notebook. Heart rhythm indices, including time-domain, frequency-domain, and nonlinear indices, were computed for each time point from the rhythmogram — NN-interval sequence — using the “hrv-analysis” package. The study employed Student’s t-test to compare indices for varying levels of sleepiness based on integral scores, where “low level” was defined as sl 0.45 and “high level” was defined as sl 0.55. Additionally, the Pearson criterion was used to evaluate the correlation between sl and heart rate indices at each time interval. The indices responsible for the variability of the NN-interval sequence, namely NNi_50 (p=0.027), NNi_20 (p=0.007), and pNNi_20 (p=0.024), exhibited lower values during periods of “low” sleepiness (N=54) as compared to “high” sleepiness (N=58). Moreover, we observed that the autonomic balance index, i.e., the ratio of the power of the heart rate variability spectrum in the low-frequency band to that in the high-frequency band, was higher during ‘high’ sleepiness (p=0.015). Analysis revealed that correlations between integral sleepiness score and heart rate indices were present only for the 08:30 PM time point. Correlations of sl with the NN-interval range (R=–0.388; p=0.028), the severity of sympathetic regulatory circuit activity (R=–0.383; p=0.031), and the nonlinear cardiovagal index (R=–0.359; p=0.043) were found. Thus, it can be inferred that increased sleepiness is associated with decreased heart rate variability indices, along with decreased functioning of the autonomic nervous system overall.

Validation and interpretation of a multimodal drowsiness detection system using explainable machine learning

Background and objectiveDrowsiness behind the wheel is a major road safety issue with efforts focused on developing drowsy driving detection systems. However, most drowsy driving detection studies using physiological signals have focused on developing a 'black box' machine learning classifier, with much less focus on 'robustness' and 'explainability'—two crucial properties of a trustworthy machine learning model. Therefore, this study has focused on using multiple validation techniques to evaluate the overall performance of such a system using multiple supervised machine learning-based classifiers and then unbox the black box model using explainable machine learning. MethodsDriving was simulated via a 30-minute psychomotor vigilance task while the participants reported their level of subjective sleepiness with their physiological signals: electroencephalogram (EEG), electrooculogram (EOG) and electrocardiogram (ECG) being recorded. Six different techniques, comprising subject-dependent and independent techniques were applied for model validation and robustness testing with three supervised machine learning classifiers, namely K-nearest neighbours (KNN), support vector machines (SVM) and random forest (RF), and two explainable methods, namely SHapley Additive exPlanation (SHAP) analysis and partial dependency analysis (PDA) were leveraged for model interpretation. ResultsThe study identified the leave one participant out, a subject-independent validation technique to be most useful, with the best sensitivity of 70.3 %, specificity of 82.2 %, and an accuracy of 80.1 % using the random forest classifier in addressing the autocorrelation issue due to inter-individual differences in physiological signals. Moreover, the explainable results suggest most important physiological features for drowsiness detection, with a clear cut-off in the decision boundary. ConclusionsThe implication of the study will ensure a rigorous validation for robustness testing and an explainable machine learning approach to developing a trustworthy drowsiness detection system and enhancing road safety. The explainable machine learning-based results show promise in real-life deployment of the physiological-signal based in-vehicle trustworthy drowsiness detection system, with higher reliability and explainability, along with a lower system cost.

An on-road examination of daytime and evening driving on rural roads: physiological, subjective, eye gaze, and driving performance outcomes.

Experiencing sleepiness when driving is associated with increased crash risk. An increasing number of studies have examined on-road driver sleepiness; however, these studies typically assess the effect of sleepiness during the late night or early morning hours when sleep pressure is approaching its greatest. An on-road driving study was performed to assess how a range of physiological and sleepiness measures are impacted when driving during the daytime and evening when moderate sleepiness is experienced. In total, 27 participants (14 women and 13 men) completed a driving session in a rural town lasting approximately 60 minutes, while physiological sleepiness (heart rate variability), subjective sleepiness, eye tracking data, vehicle kinematic data and GPS speed data were recorded. Daytime driving sessions began at 12:00 or 14:00, with the evening sessions beginning at 19:30 or 20:30; only a subset of participants (n = 11) completing the evening sessions (daytime and evening order counterbalanced). The results suggest reductions in the horizontal and vertical scanning ranges occurred during the initial 40 minutes of driving for both daytime and evening sessions, but with evening sessions reductions in scanning ranges occurred across the entire driving session. Moreover, during evening driving there was an increase in physiological and subjective sleepiness levels. The results demonstrate meaningful increases in sleepiness and reductions in eye scanning when driving during both the daytime and particularly in the evening. Thus, drivers need to remain vigilant when driving during the daytime and the evening.

Circadian and homeostatic sleep-wake regulation of secretory immunoglobulin A (sIgA): Effects of environmental light and recovery sleep

Secretory Immunoglobulin A (sIgA) builds the first line of the human immune defense. It is not clear whether the power of this defence line is constant across the 24-h day, depends on sleep pressure levels and can be influenced by external lighting conditions. Thus, in 10 healthy young volunteers, we retrospectively analyzed saliva samples for sIgA levels under strictly controlled laboratory conditions across 40 ​h of extended wakefulness under two lighting conditions (dim light 8 lx and blue-enriched light 250 lx, 9000 ​K) to test for circadian and homeostatic sleep-wake influences. We compared the temporal profile of sIgA with the circadian time course of melatonin and cortisol along with subjective sleepiness levels, assessed in the same study by Gabel et al. (2017). The 40-h time course of sIgA exhibited a clear circadian modulation with peak values in the mornings coinciding with the individuals' habitual rise-time. In addition, sIgA levels progressively increased throughout the 40 ​h of extended wakefulness and were temporally correlated with subjective sleepiness but not with subjective ratings of tension and discomfort. In contrast to the circadian profile of melatonin and cortisol, sIgA levels were not significantly altered by the lighting conditions. Unexpectedly, sIgA levels in the morning after recovery sleep from 40 ​h of extended wakefulness rose considerably by more than an order of magnitude (10 times more) compared to morning levels after baseline sleep. We have evidence that diurnal sIgA levels in humans are regulated by the circadian timing system, and challenging the status of the sleep-wake homeostat (i.e. extended wakefulness) boosts human sIgA levels. Thus, besides a person's circadian phase position, the first line of human immune defense also strongly depends on the person's sleep-wake history and actual sleepiness levels. In sum, the fight against pathogenic microorganisms by a key immunological component (sIgA) is modulated by two fundamental processes implicated in human sleep-wake regulation.

Winter-summer difference in post-awakening salivary α-amylase and sleepiness depending on sleep and melatonin

Winter and summer seasons are contrasted by light/dark conditions at temperate latitudes, and the negative influence of this contrast on circadian health is yet to be quantified. This field study (performed in Novosibirsk, 55°N, no daylight saving time transitions) aimed to compare post-awakening arousal state in summer and winter in subjects (N=45) on a fixed 5-workday schedule (waken up by alarm at either ∼6 am or ∼7 am). Their circadian status (by 24-h melatonin profiles) and sleep (by log data) have been previously reported. Salivary α-amylase levels (a biomarker of the sympathetic nervous system activity, or stress) and subjective sleepiness were measured immediately after awakening on Friday, at minute 0 (supine), 10, 20, and 30 (not supine). α-Amylase levels were found to be higher in winter, along with a blunted α-amylase awakening response (AAR; a decline from minute 0 to minute 10 value). Both effects were attributable mainly to the 7am group. Sleepiness levels also increased in winter, mainly due to the seasonally dependent subjects, and predictably associated with shorter, later sleep, and later melatonin circadian phase. The sleepiness and α-amylase changes did not correlate. The seasonal change in α-amylase was positively associated with the change in the amount of melatonin secreted, probably reflecting the parallelism in the noradrenergic neural control of both α-amylase and melatonin secretion. Together, higher post-awakening salivary α-amylase levels (indicating stress) and subjective sleepiness levels (indicating greater sleep need) in winter compared to summer point to a less healthy state in winter.

Sleep-deprived residents and rapid picture naming performance using the Mobile Universal Lexicon Evaluation System (MULES) test.

ObjectiveThe Mobile Universal Lexicon Evaluation System (MULES) is a rapid picture naming task that captures extensive brain networks involving neurocognitive, afferent/efferent visual, and language pathways. Many of the factors captured by MULES may be abnormal in sleep-deprived residents. This study investigates the effect of sleep deprivation in post-call residents on MULES performance.MethodsMULES, consisting of 54 color photographs, was administered to a cohort of neurology residents taking 24-hour in-hospital call (n = 18) and a group of similar-aged controls not taking call (n = 18). Differences in times between baseline and follow-up MULES scores were compared between the two groups.ResultsMULES time change in call residents was significantly worse (slower) from baseline (mean 1.2 s slower) compared to non-call controls (mean 11.2 s faster) (P < 0.001, Wilcoxon rank sum test). The change in MULES time from baseline was significantly correlated to the change in subjective level of sleepiness for call residents and to the amount of sleep obtained in the 24 h prior to follow-up testing for the entire cohort. For call residents, the duration of sleep obtained during call did not significantly correlate with change in MULES scores. There was no significant correlation between MULES change and sleep quality questionnaire score for the entire cohort.ConclusionThe MULES is a novel test for effects of sleep deprivation on neurocognition and vision pathways. Sleep deprivation significantly worsens MULES performance. Subjective sleepiness may also affect MULES performance. MULES may serve as a useful performance assessment tool for sleep deprivation in residents.

Acute cognitive effects of the hypocretin receptor antagonist almorexant relative to zolpidem and placebo: a randomized clinical trial.

Hypnotic medications can adversely affect behavior during unanticipated awakenings during the night. Animals treated with the hypocretin (Hcrt) receptor antagonist almorexant (ALM) have less acute cognitive impairment compared to the GABAA receptor modulator zolpidem (ZOL). This study aimed to determine whether ALM produces less acute cognitive impairment than ZOL in human subjects. Healthy, young adult, unmedicated male and female subjects participated in a controlled trial of a single dose of ALM 100 mg (N = 48), ALM 200 mg (N = 53), ZOL 10 mg (N = 49), and placebo (PBO, N = 52). ZOL and both doses of ALM produced similar levels of subjective sleepiness and impaired the ability of subjects to remain awake in a dark, low-stimulus setting relative to PBO. For most cognitive measures, performance under ZOL was significantly worse than ALM or PBO. For tasks involving verbal memory or visual-motor coordination, ZOL impaired performance, whereas the two doses of ALM were no different than PBO. For tasks involving higher-order executive function, ZOL produced impairment in processing speed and inhibitory control, whereas the two doses of ALM were no different than PBO. Performance decrements for ALM were less than ZOL but greater than PBO for some reaction time measures. The data provide support for the hypothesis that Hcrt receptor antagonists produce less functional impairment than a benzodiazepine receptor agonist (BzRA). These observations are particularly relevant to patients treated with sedative-hypnotics who are at elevated risk for falls and other untoward events during the intended hours for sleep.

The impact of driver sleepiness on fixation-related brain potentials.

The effects of driver sleepiness are often quantified as deteriorated driving performance, increased blink durations and high levels of subjective sleepiness. Driver sleepiness has also been associated with increasing levels of electroencephalogram (EEG) power, especially in the alpha range. The present exploratory study investigated a new measure of driver sleepiness, the EEG fixation-related lambda response. Thirty young male drivers (23.6±1.7years old) participated in a driving simulator experiment in which they drove on rural and suburban roads in simulated daylight versus darkness during both the daytime (full sleep) and night-time (sleep deprived). The results show lower lambda responses during night driving and with longer time on task, indicating that sleep deprivation and time on task cause a general decrement in cortical responsiveness to incoming visual stimuli. Levels of subjective sleepiness and line crossings were higher under the same conditions. Furthermore, results of a linear mixed-effects model showed that low lambda responses are associated with high subjective sleepiness and more line crossings. We suggest that the fixation-related lambda response can be used to investigate driving impairment induced by sleep deprivation while driving and that, after further refinement, it may be useful as an objective measure of driver sleepiness.

Baseline Pupil Diameter Is Not a Reliable Biomarker of Subjective Sleepiness.

Sleepiness is commonly seen as reflecting the basic physiological need to sleep and is associated with physiological and neurobiological changes. Subjective evaluations of sleepiness, however, are neither representative of cognitive and physical performances, nor of physiological sleepiness. Finding a simple, rapid, and objective marker of sleepiness is essential in order to prevent errors and accidents, but this has remained largely unsuccessful. The aim of this study was to determine whether the baseline pupil diameter is a physiological biomarker of sleepiness at all times of day and to isolate the regulatory components involved. Twelve healthy men (20–29 years old) participated in a 56-h experimental protocol, including a 34-h constant routine paradigm with enforced wakefulness. This protocol was used in order to eliminate the potential influence of all environmental rhythms and reveal the endogenous circadian rhythmicity of two physiological measures: sleepiness and pupil diameter. Sleepiness was assessed subjectively every hour on a computerized 10 cm visual analog scale and pupil size was recorded every 2 h with a hand-held video-pupilometer. Our results revealed that subjective sleepiness increased linearly with time awake and displayed a circadian rhythm. Baseline pupil diameter showed a linear decrease with time spent awake as well as a circadian 24-h rhythm. This is the first evidence of a circadian variation of the baseline pupil size in a highly-controlled constant routine paradigm conducted in very dim light conditions. An overall negative correlation between the size of the pupil and the subjective level of sleepiness was observed. Analyzing the contribution of the two sleep regulation components in this correlation, we further showed: (1) a negative correlation between the homeostatic sleep pressure components, (2) a negative correlation between the circadian drives only during half of the 24 hours, corresponding to 62% of the biological day and 25% of the biological night. These results highlight that, due to the dual regulation of sleepiness by the homeostatic and circadian processes, baseline pupil diameter is an index of sleepiness only at certain times and therefore cannot be used as a systematic and reliable biomarker of sleepiness.

Differential effects of split and continuous sleep on neurobehavioral function and glucose tolerance in sleep-restricted adolescents.

Study ObjectivesMany adolescents are exposed to sleep restriction on school nights. We assessed how different apportionment of restricted sleep (continuous vs. split sleep) influences neurobehavioral function and glucose levels.MethodsAdolescents, aged 15–19 years, were evaluated in a dormitory setting using a parallel-group design. Following two baseline nights of 9-hour time-in-bed (TIB), participants underwent either 5 nights of continuous 6.5-h TIB (n = 29) or 5-hour nocturnal TIB with a 1.5-hour afternoon nap (n = 29). After two recovery nights of 9-hour TIB, participants were sleep restricted for another three nights. Sleep was assessed using polysomnography (PSG). Cognitive performance and mood were evaluated three times per day. Oral glucose tolerance tests (OGTT) were conducted on mornings after baseline sleep, recovery sleep, and the third day of each sleep restriction cycle.ResultsThe split sleep group had fewer vigilance lapses, better working memory and executive function, faster processing speed, lower level of subjective sleepiness, and more positive mood, even though PSG-verified total sleep time was less than the continuous sleep group. However, vigilance in both sleep-restricted groups was inferior to adolescents in a prior sample given 9-hour nocturnal TIB. During both cycles of sleep restriction, blood glucose during the OGTT increased by a greater amount in the split sleep schedule compared with persons receiving 6.5-hour continuous sleep.ConclusionsIn adolescents, modest multinight sleep restriction had divergent negative effects on cognitive performance and glucose levels depending on how the restricted sleep was apportioned. They are best advised to obtain the recommended amount of nocturnal sleep.Trial registration https://clinicaltrials.gov/ct2/show/NCT03333512

Chronic sleep restriction greatly magnifies performance decrements immediately after awakening.

Sleep inertia, subjectively experienced as grogginess felt upon awakening, causes cognitive performance impairments that can require up to 1.5 hr to dissipate. It is unknown, however, how chronic sleep restriction (CSR) influences the magnitude and duration of sleep inertia-related performance deficits. Twenty-six healthy participants were enrolled in one of two in-laboratory sleep restriction protocols (one 32 day randomized control and one 38 day protocol) that separated the influence of sleep and circadian effects on performance using different "day"-lengths (20 and 42.85 hr day-lengths, respectively). The sleep opportunity per 24 hr day was the equivalent of 5.6 hr for each CSR condition and 8 hr for the Control condition. Participant's performance and subjective sleepiness were assessed within ~2 min after electroencephalogram-verified awakening and every 10 min thereafter for 70 min to evaluate performance and subjective sleepiness during sleep inertia. Performance within 2 min of awakening was ~10% worse in CSR conditions compared with Control and remained impaired across the dissipation of sleep inertia in the CSR conditions when compared with Control. These impairments in performance during sleep inertia occurred after only chronic exposure to sleep restriction and were even worse after awakenings during the biological nighttime. Interestingly, despite differences in objective performance, there were no significant differences between groups in subjective levels of sleepiness during sleep inertia. CSR worsens sleep inertia, especially for awakenings during the biological night. These findings are important for individuals needing to perform tasks quickly upon awakening, particularly those who obtain less than 6 hr of sleep on a nightly basis. The study "Sleep Duration Required to Restore Performance During Chronic Sleep Restriction" was registered as a clinical trial (#NCT01581125) at clinicaltrials.gov (https://clinicaltrials.gov/ct2/show/NCT01581125?term=NCT01581125.&rank=1).

Effects of circadian misalignment on cognition in chronic shift workers

Shift work is associated with increased human operational errors, presumably due to the circadian timing system that inhibits optimal cognitive function during the night. Circadian misalignment, which is the misalignment between the circadian pacemaker and behavioral/environmental cycles, impairs cognitive performance in non-shift workers. However, it remains uncertain whether the adverse cognitive consequences of circadian misalignment are also observed in chronic shift workers. Thus, we investigated the effects of circadian misalignment on cognitive performance in chronic shift workers. Using a randomized, cross-over design that simulated day shift work (circadian alignment) and night shift work (circadian misalignment), we show that circadian misalignment increases cognitive vulnerability on sustained attention, information processing and visual-motor performance, particularly after more than 10 hours of scheduled wakefulness. Furthermore, their increased levels of subjective sleepiness and their decreased sleep efficiency were significantly associated with impaired sustained attention and visual-motor performance. Our data suggest that circadian misalignment dramatically deteriorates cognitive performance in chronic shift workers under circadian misalignment. This increased cognitive vulnerability may have important safety consequences, given the increasing number of nighttime jobs that crucially rely on the availability of cognitive resources.

Young adults are more vulnerable to chronic sleep deficiency and recurrent circadian disruption than older adults

More than a third of US adults report fewer than 6 hours of sleep a night, making chronic sleep restriction a growing public health concern. Sleep curtailment is associated with an increase in industrial accidents, motor vehicle accidents, medical and other occupational errors. Young adults are more vulnerable to acute sleep deprivation than older adults, but less is known about how young vs. older adults respond to the more commonly experienced chronic sleep restriction. To test the hypothesis that young adults are more vulnerable to chronic sleep loss than older adults, we compared data from young and older adults who underwent three weeks of chronic sleep restriction (equivalent to 5.6 hours/24 hours) combined with recurrent circadian disruption in an experiment that enabled us to separate the influences of the sleep-wake homeostatic process, the circadian timing system, and the chronic sleep deficit. We found that while young and older adults reported similar levels of subjective sleepiness, objective measures of sleepiness revealed that young adults were more vulnerable and had more attentional failures than the older adults. These results have important public health implications, particularly related to prevention of sleep-related motor vehicle crashes in young drivers. Further research is needed to understand the neurobiological basis of these age-related differences.

Sustained benefits of delaying school start time on adolescent sleep and well-being

Study ObjectivesTo investigate the short- and longer-term impact of a 45-min delay in school start time on sleep and well-being of adolescents.MethodsThe sample consisted of 375 students in grades 7–10 (mean age ± SD: 14.6 ± 1.15 years) from an all-girls’ secondary school in Singapore that delayed its start time from 07:30 to 08:15. Self-reports of sleep timing, sleepiness, and well-being (depressive symptoms and mood) were obtained at baseline prior to the delay, and at approximately 1 and 9 months after the delay. Total sleep time (TST) was evaluated via actigraphy.ResultsAfter 1 month, bedtimes on school nights were delayed by 9.0 min, while rise times were delayed by 31.6 min, resulting in an increase in time in bed (TIB) of 23.2 min. After 9 months, the increase in TIB was sustained, and TST increased by 10.0 min relative to baseline. Participants also reported lower levels of subjective sleepiness and improvement in well-being at both follow-ups. Notably, greater increase in sleep duration on school nights was associated with greater improvement in alertness and well-being.ConclusionsDelaying school start time can result in sustained benefits on sleep duration, daytime alertness, and mental well-being even within a culture where trading sleep for academic success is widespread.

How does long trip affect on driving performance, eye blinks and awareness of sleepiness among commercial drivers? A naturalistic driving test study

A total of 120 commercial drivers from four age groups participated in the expressway driving test in Shandong, China to perform 2, 3, and 4 h continuous driving tasks and collect the data on the driver's blinking, driving performance and self-reported level of sleepiness. Two-way repeated measures ANOVA was used to evaluate the effects of driving duration on the variation of the eye-blink behavior, driving performance and subjective feeling of sleepiness across the different age groups over the time periods tested. Additionally, Pearson product-moment correlation was used to quantify the association between the variations of the dependent variables. The results showed that there was significant difference between groups, significant effect over time and significant interaction between the age and driving duration in the variations of the driver’s blink frequency, blink duration, closure duration, speed perception, choice reaction time, number of incorrect action judgments and subjective level of sleepiness. However, a significant difference varied over time, but no effect of the interaction between groups and time were found in the variation of the driver’s attention allocation value. Furthermore, driver’s eye blink measures were more sensitive to sleepiness and older drivers were more likely to get sleepy in long distance driving.

Effects of Prolonged Tasks and Rest Patterns on Driver's Visual Behaviors, Driving Performance, and Sleepiness Awareness in Tunnel Environments: A Simulator Study

Driving sleepiness is one of the most important potential causes of traffic accidents, especially for long-distance drivers under monotonous conditions. In this study, 68 professional, male coach drivers were recruited to participate in 2-, 3-, and 4-h driving tasks on a simulated mountainous expressway and then were given a 15- or 30-min rest with or without music stimulus to recover. At the end of each driving task and rest period, the driver’s eye movement indicators, driving performance measures, and subjective sleepiness level were examined via eye tracking device, performance testers, and the Stanford Sleepiness Scale, respectively. One-way ANOVA was used to analyze the variation of each variable at different stages. The statistical analysis revealed that the driving duration and rest patterns have significant impacts on the driver’s visual behaviors and driving performance. The participants’ blink duration, eye closure duration, reaction time, number of incorrect action judgments, and subjective level of sleepiness significantly changed as driving time increased. Drivers recovered sufficiently after a general 30-min rest or a 15-min rest with music after 2- and 3-h driving tasks, but required a 30-min rest with music as stimulus after 4-h driving task. These results provide insight into potential strategies for traffic safety improvements among long-distance drivers.

Can variations in visual behavior measures be good predictors of driver sleepiness? A real driving test study

ABSTRACTObjective: The primary purpose of this study was to examine the association between variations in visual behavior measures and subjective sleepiness levels across age groups over time to determine a quantitative method of measuring drivers' sleepiness levels.Method: A total of 128 volunteer drivers in 4 age groups were asked to finish 2-, 3-, and 4-h continuous driving tasks on expressways, during which the driver's fixation, saccade, and blink measures were recorded by an eye-tracking system and the subjective sleepiness level was measured through the Stanford Sleepiness Scale. Two-way repeated measures analysis of variance was then used to examine the change in visual behavior measures across age groups over time and compare the interactive effects of these 2 factors on the dependent visual measures.Results: Drivers' visual behavior measures and subjective sleepiness levels vary significantly over time but not across age groups. A statistically significant interaction between age group and driving duration was found in drivers' pupil diameter, deviation of search angle, saccade amplitude, blink frequency, blink duration, and closure duration. Additionally, change in a driver's subjective sleepiness level is positively or negatively associated with variation in visual behavior measures, and such relationships can be expressed in regression models for different period of driving duration.Conclusions: Driving duration affects drivers' sleepiness significantly, so the amount of continuous driving time should be strictly controlled. Moreover, driving sleepiness can be quantified through the change rate of drivers' visual behavior measures to alert drivers of sleepiness risk and to encourage rest periods. These results provide insight into potential strategies for reducing and preventing traffic accidents and injuries.

Do repeated rumble strip hits improve driver alertness?

Driving while sleepy is associated with increased crash risk. Rumble strips are designed to alert a sleepy or inattentive driver when they deviate outside their driving lane. The current study sought to examine the effects of repeated rumble strip hits on levels of physiological and subjective sleepiness as well as simulated driving performance. In total, 36 regular shift workers drove a high-fidelity moving base simulator on a simulated road with rumble strips installed at the shoulder and centre line after a working a full night shift. The results show that, on average, the first rumble strip occurred after 20 min of driving, with subsequent hits occurring 10 min later, with the last three occurring approximately every 5 min thereafter. Specifically, it was found that the first rumble strip hit reduced physiological sleepiness; however, subsequent hits did not increase alertness. Moreover, the results also demonstrate that increased subjective sleepiness levels, via the Karolinska Sleepiness Scale, were associated with a greater probability of hitting a rumble strip. The present results suggest that sleepiness is very resilient to even strongly arousing stimuli, with physiological and subjective sleepiness increasing over the duration of the drive, despite the interference caused by rumble strips.

At-sea trial of 24-h-based submarine watchstanding schedules with high and low correlated color temperature light sources.

United States Navy submariners have historically lived with circadian disruption while at sea due to 18-h-based watchschedules. Previous research demonstrated that circadian entrainment improved with 24-h-based watchschedules. Twenty-nine male crew members participated in the study, which took place on an actual submarine patrol. The crew were exposed, first, to experimental high correlated color temperature (CCT = 13,500 K) fluorescent light sources and then to standard-issue fluorescent light sources (CCT = 4100 K). A variety of outcome measures were employed to determine if higher levels of circadian-effective light during on-watch times would further promote behavioral alignment to 24-h-based watchschedules. The high CCT light source produced significantly higher circadian light exposures than the low CCT light source, which was associated with significantly greater 24-h behavioral alignment with work schedules using phasor analysis, greater levels of sleep efficiency measured with wrist actigraphy, lower levels of subjective sleepiness measured with the Karolinska Sleepiness Scale, and higher nighttime melatonin concentrations measured by morning urinary 6-sulfatoxymelatonin/creatinine ratios. Unlike these diverse outcome measures, performance scores were significantly worse under the high CCT light source than under the low CCT light source, due to practice effects. As hypothesized, with the exception of the performance scores, all of the data converge to suggest that high CCT light sources, combined with 24-h watchschedules, promote better behavioral alignment with work schedules and greater sleep quality on submarines. Since the order and the type of light sources were confounded in this field study, the results should only be considered as consistent with our theoretical understanding of how regular, 24-h light-dark exposures combined with high circadian light exposures can promote greater behavioral alignment with work schedules and with sleep.