Stop and revive? : the effectiveness of nap and active rest breaks for reducing driver sleepiness

The incidence of sleep-related crashes has been estimated to account for approximately 20% of all fatal and severe crashes. The use of sleepiness countermeasures by drivers is an important component to reduce the incidence rates of sleep-related crashes. Taking a brief nap and stopping for a rest break are two highly publicised countermeasures for driver sleepiness and are also believed by drivers to be the most effective countermeasures. Despite this belief, there is scarce evidence to support the utility of these countermeasures for reducing driver sleepiness levels. Therefore, determining the effectiveness of these countermeasures is an important road safety concern. The current study utilised a young adult sample (N = 20) to investigate the effectiveness of a nap and an active rest break. The countermeasures effects were evaluated by physiological, behavioural (hazard perception skill), and subjective measures previously found sensitive to sleepiness. Participants initially completed two hours of a simulated driving task followed by a 15 minute nap opportunity or a 15 minute active rest break that included 10 minutes of brisk walking. After the break, participants completed one final hour of the simulated driving task. A within-subjects design was used so that each participant completed both the nap and the active rest break conditions on separate occasions. The analyses revealed that only the nap break provided any meaningful reduction in physiological sleepiness, reduced subjective sleepiness levels, and maintained hazard perception performance. In contrast, the active rest break had no effect for reducing physiological sleepiness and resulted in a decrement in hazard perception performance (i.e., an increase of reaction time latencies), with a transient reduction in subjective sleepiness levels. A number of theoretical, empirical and practical issues were identified by the current study.

Stop and revive? The effectiveness of nap and active rest breaks for reducing driver sleepiness

Objectives The purpose for this study was to determine the relative benefit of nap and active rest breaks for reducing driver sleepiness. Methods Participants were 20 healthy young adults (20-25 years), including 8 males and 12 females. A counterbalanced within-subjects design was used such that each participant completed both conditions on separate occasions, a week apart. The effects of the countermeasures were evaluated by established physiological (EEG theta and alpha absolute power), subjective (Karolinska Sleepiness Scale), and driving performance measures (Hazard Perception Task). Participants woke at 5am, and undertook a simulated driving task for two hours; each participant then had either a 15-minute nap opportunity or a 15-minute active rest break that included 10 minutes of brisk walking, followed by another hour of simulated driving. Results The nap break reduced EEG theta and alpha absolute power and eventually reduced subjective sleepiness levels. In contrast, the active rest break did not reduce EEG theta and alpha absolute power levels with the power levels eventually increasing. An immediate reduction of subjective sleepiness was observed, with subjective sleepiness increasing during the final hour of simulated driving. No difference was found between the two breaks for hazard perception performance. Conclusions Only the nap break produced a significant reduction in physiological sleepiness. The immediate reductions of subjective sleepiness following the active rest break could leave drivers with erroneous perceptions of their sleepiness, particularly as physiological sleepiness continued to increase after the break.

Stop and revive? The effectiveness of nap and active rest breaks for reducing drivers sleepiness

The purpose of this study was to compare the effects of two commonly utilised sleepiness countermeasures: a nap break and an active rest break. The effects of the countermeasures were evaluated by physiological (EEG), subjective, and driving performance measures. Participants completed two hours of simulated driving, followed by a 15 minute nap break or a 15 minute active rest break then completed the final hour of simulated driving. The nap break reduced EEG and subjective sleepiness. The active rest break did not reduce EEG sleepiness, with sleepiness levels eventually increasing, and resulted in an immediate reduction of subjective sleepiness. No difference was found between the two breaks for the driving performance measure. The immediate reduction of subjective sleepiness after the active rest break could leave drivers with erroneous perceptions of their sleepiness, particularly with increases of physiological sleepiness after the break.

Driver sleepiness self-regulation : physiological and subjective evidence

Introduction: Sleepiness contributes to a substantial proportion of fatal and severe road crashes. Efforts to reduce the incidence of sleep-related crashes have largely focussed on driver education to promote self-regulation of driving behaviour. However, effective self-regulation requires accurate self-perception of sleepiness. The aim of this study was to assess capacity to accurately identify sleepiness, and self-regulate driving cessation, during a validated driving simulator task. Methods: Participants comprised 26 young adult drivers (20-28 years) who had open licenses. No other exclusion criteria where used. Participants were partially sleep deprived (05:00 wake up) and completed a laboratory-based hazard perception driving simulation, counterbalanced to either at mid-morning or mid-afternoon. Established physiological measures (i.e., EEG, EOG) and subjective measures (Karolinska Sleepiness Scale), previously found sensitive to changes in sleepiness levels, were utilised. Participants were instructed to ‘drive’ on the simulator until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 36.1 minutes (±17.7 minutes). Subjective sleepiness increased significantly from the beginning (KSS=6.6±0.7) to the end (KSS=8.2±0.5) of the driving period. No significant differences were found for EEG spectral power measures of sleepiness (i.e., theta or alpha spectral power) from the start of the driving task to the point of cessation of driving. During the nap opportunity, 88% of the participants (23/26) were able to reach sleep onset with an average latency of 9.9 minutes (±7.5 minutes). The average nap duration was 15.1 minutes (±8.1 minutes). Sleep architecture during the nap was predominately comprised of Stages I and II (combined 92%). Discussion: Participants reported high levels of sleepiness during daytime driving after very moderate sleep restriction. They were able to report increasing sleepiness during the test period despite no observed change in standard physiological indices of sleepiness. This increased subjective sleepiness had behavioural validity as the participants had high ‘napability’ at the point of driving cessation, with most achieving some degree of subsequent sleep. This study suggests that the nature of a safety instruction (i.e. how to view sleepiness) can be a determinant of driver behaviour.

Too sleepy to drive : self-perception and regulation of driving when sleepy

Background: Sleepiness is a direct contributor to a substantial proportion of fatal and severe road cashes. A number of technological solutions designed to detect sleepiness have been developed, but self-awareness of increasing sleepiness remains a critical component in on-road strategies for mitigating this risk. In order to take appropriate action when sleepy, drivers’ perceptions of their level of sleepiness must be accurate. Aims: This study aimed to assess capacity to accurately identify sleepiness and self-regulate driving cessation during a validated driving simulator task. Participants: Participants comprised 26 young adult drivers (20-28 years). The drivers had open licenses but no other exclusion criteria where used. Methods: Participants woke at 5am, and took part in a laboratory-based hazard perception driving simulation, either at mid-morning or mid-afternoon. Established physiological measures (including EEG) and subjective measures (sleepiness ratings) previously found sensitive to changes in sleepiness levels were utilised. Participants were instructed to ‘drive’ until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 39 minutes (±18 minutes). Almost all (23/26) of the participants then achieved sleep during the nap opportunity. These data suggest that the participants’ perceptions of sleepiness were specific. However, EEG data from a number of participants suggested very high levels of sleepiness prior to driving cessation, suggesting poor sensitivity. Conclusions: Participants reported high levels of sleepiness while driving after very moderate sleep restriction. They were able to identify increasing sleepiness during the test period, could decide to cease driving and in most cases were sufficiently sleepy to achieve sleep during the daytime session. However, the levels of sleepiness achieved prior to driving cessation suggest poor accuracy in self-perception and regulation. This presents practical issues for the implementation of fatigue and sleep-related strategies to improve driver safety.

Efficacy of proxy definitions for identification of fatigue/sleep-related crashes : an Australian evaluation

Fatigue/sleepiness is recognised as an important contributory factor in fatal and serious injury road traffic incidents (RTIs), however, identifying fatigue/sleepiness as a causal factor remains an uncertain science. Within Australia attending police officers at a RTI report the causal factors; one option is fatigue/sleepiness. In some Australian jurisdictions police incident databases are subject to post hoc analysis using a proxy definition for fatigue/sleepiness. This secondary analysis identifies further RTIs caused by fatigue/sleepiness not initially identified by attending officers. The current study investigates the efficacy of such proxy definitions for attributing fatigue/sleepiness as a RTI causal factor. Over 1600 Australian drivers were surveyed regarding their experience and involvement in fatigue/sleep-related RTIs and near-misses during the past five years. Driving while fatigued/sleepy had been experienced by the majority of participants (66.0% of participants). Fatigue/sleep-related near misses were reported by 19.1% of participants, with 2.4% being involved in a fatigue/sleep-related RTI. Examination of the characteristics for the most recent event (either a near miss or crash) found that the largest proportion of incidents (28.0%) occurred when commuting to or from work, followed by social activities (25.1%), holiday travel (19.8%), or for work purposes (10.1%). The fatigue/sleep related RTI and near-miss experience of a representative sample of Australian drivers does not reflect the proxy definitions used for fatigue/sleepiness identification. In particular those RTIs that occur in urban areas and at slow speeds may not be identified. While important to have a strategy for identifying fatigue/sleepiness related RTIs proxy measures appear best suited to identifying specific subsets of such RTIs.

Can postural control performance be an indicator of truck drivers' sleep deprivation?

Long-haul drivers work in irregular schedules due to load delivery demands. In general, driving and sleeping occur at irregular times and, consequently, partial sleep deprivation and/or circadian misalignment may emerge and result in sleepiness at the wheel. In this way, the aim of this study was to verify changes in the postural control parameters of professional drivers after one-night working. Eight male truck drivers working at night - night drivers (ND) and nine day drivers (DD) volunteered to participate in this study. The night drivers' postural stability was assessed immediately before and after an approximately 430 km journey by two identical force platforms at departure and arrival sites. The DD group was measured before and after a day's work. An interaction effect of time of day and type of shift in both conditions: eyes open (p < 0.01) and eyes closed (p < 0.001) for amplitude of mediolateral movements was observed. Postural stability, measured by force platform, is affected by a night of work, suggesting that it could be an effect of circadian and homeostatic influences over postural control.

Frontal Lobe Function and Performance Monitoring following Total Sleep Deprivation

Imaging studies have shown reduced frontal lobe resources following total sleep deprivation (TSD). The anterior cingulate cortex (ACC) in the frontal region plays a role in performance monitoring and cognitive control; both error detection and response inhibition are impaired following sleep loss. Event-related potentials (ERPs) are an electrophysiological tool used to index the brain's response to stimuli and information processing. In the Flanker task, the error-related negativity (ERN) and error positivity (Pe) ERPs are elicited after erroneous button presses. In a Go/NoGo task, NoGo-N2 and NoGo-P3 ERPs are elicited during high conflict stimulus processing. Research investigating the impact of sleep loss on ERPs during performance monitoring is equivocal, possibly due to task differences, sample size differences and varying degrees of sleep loss. Based on the effects of sleep loss on frontal function and prior research, it was expected that the sleep deprivation group would have lower accuracy, slower reaction time and impaired remediation on performance monitoring tasks, along with attenuated and delayed stimulus- and response-locked ERPs. In the current study, 49 young adults (24 male) were screened to be healthy good sleepers and then randomly assigned to a sleep deprived (n = 24) or rested control (n = 25) group. Participants slept in the laboratory on a baseline night, followed by a second night of sleep or wake. Flanker and Go/NoGo tasks were administered in a battery at 1O:30am (i.e., 27 hours awake for the sleep deprivation group) to measure performance monitoring. On the Flanker task, the sleep deprivation group was significantly slower than controls (p's <.05), but groups did not differ on accuracy. No group differences were observed in post-error slowing, but a trend was observed for less remedial accuracy in the sleep deprived group compared to controls (p = .09), suggesting impairment in the ability to take remedial action following TSD. Delayed P300s were observed in the sleep deprived group on congruent and incongruent Flanker trials combined (p = .001). On the Go/NoGo task, the hit rate (i.e., Go accuracy) was significantly lower in the sleep deprived group compared to controls (p <.001), but no differences were found on false alarm rates (i.e., NoGo Accuracy). For the sleep deprived group, the Go-P3 was significantly smaller (p = .045) and there was a trend for a smaller NoGo-N2 compared to controls (p = .08). The ERN amplitude was reduced in the TSD group compared to controls in both the Flanker and Go/NoGo tasks. Error rate was significantly correlated with the amplitude of response-locked ERNs in control (r = -.55, p=.005) and sleep deprived groups (r = -.46, p = .021); error rate was also correlated with Pe amplitude in controls (r = .46, p=.022) and a trend was found in the sleep deprived participants (r = .39, p =. 052). An exploratory analysis showed significantly larger Pe mean amplitudes (p = .025) in the sleep deprived group compared to controls for participants who made more than 40+ errors on the Flanker task. Altered stimulus processing as indexed by delayed P3 latency during the Flanker task and smaller amplitude Go-P3s during the Go/NoGo task indicate impairment in stimulus evaluation and / or context updating during frontal lobe tasks. ERN and NoGoN2 reductions in the sleep deprived group confirm impairments in the monitoring system. These data add to a body of evidence showing that the frontal brain region is particularly vulnerable to sleep loss. Understanding the neural basis of these deficits in performance monitoring abilities is particularly important for our increasingly sleep deprived society and for safety and productivity in situations like driving and sustained operations.

Sleep deprivation affects sensorimotor coupling in postural control of young adults

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Selective REM sleep deprivation in narcolepsy

Narcolepsy is characterized by excessive daytime sleepiness and rapid eye movement (REM) sleep abnormalities, including cataplexy. The aim of this study was to assess REM sleep pressure and homeostasis in narcolepsy. Six patients with narcolepsy and six healthy controls underwent a REM sleep deprivation protocol, including one habituation, one baseline, two deprivation nights (D1, D2) and one recovery night. Multiple sleep latency tests (MSLTs) were performed during the day after baseline and after D2. During D1 and D2 REM sleep was prevented by awakening the subjects at the first polysomnographic signs of REM sleep for 2 min. Mean sleep latency and number of sleep-onset REM periods (SOREMs) were determined on all MSLT. More interventions were required to prevent REM sleep in narcoleptics compared with control subjects during D1 (57 ± 16 versus 24 ± 10) and D2 (87 ± 22 versus 35 ± 8, P = 0.004). Interventions increased from D1 to D2 by 46% in controls and by 53% in narcoleptics (P < 0.03). Selective REM sleep deprivation was successful in both controls (mean reduction of REM to 6% of baseline) and narcoleptics (11%). Both groups had a reduction of total sleep time during the deprivation nights (P = 0.03). Neither group had REM sleep rebound in the recovery night. Narcoleptics had, however, an increase in the number of SOREMs on MSLT (P = 0.005). There was no increase in the number of cataplexies after selective REM sleep deprivation. We conclude that: (i) REM sleep pressure is higher in narcoleptics; (ii) REM sleep homeostasis is similar in narcoleptics and controls; (iii) in narcoleptics selective REM sleep deprivation may have an effect on sleep propensity but not on cataplexy.

EEG correlation and power during maintenance of wakefulness test after sleep-deprivation

To investigate whether there are any objective EEG characteristics that change significantly between specific time periods during maintenance of wakefulness test (MWT) and whether such changes are associated with the ability to appropriately communicate sleepiness.

The effect of overnight sleep deprivation after competitive rugby league matches on postmatch physiological and perceptual recovery

PURPOSE: This study examined the effects of overnight sleep deprivation on recovery following competitive rugby league matches. METHODS: Eleven male, amateur rugby league players performed two competitive matches, followed by either a normal night's sleep (~8h; CONT) or a sleep deprived night (~0h; SDEP) in a randomised fashion. Testing was conducted the morning of the match, and immediately post-match, 2h post and the next morning (16h post-match). Measures included counter-movement jump (CMJ) distance, knee extensor maximal voluntary contraction (MVC), voluntary activation (VA), venous blood creatine kinase (CK) and C-reactive protein (CRP), perceived muscle soreness and a word-colour recognition cognitive function test. Percent change between post- and 16h post-match was reported to determine the effect of the intervention the next morning. RESULTS: Large effects indicated a greater post- to 16h post-match percentage decline in CMJ distance following SDEP compared to CONT (P=0.10-0.16; d=0.95-1.05). Similarly, the percentage decline in incongruent word-colour reaction times were increased in SDEP trials (P=0.007; d=1.75). Measures of MVC did not differ between conditions (P=0.40-0.75; d=0.13-0.33), though trends for larger percentage decline in VA were detected in SDEP (P=0.19; d=0.84). Further, large effects indicated higher CK and CRP responses 16h post-match during SDEP compared to CONT (P=0.11-0.87; d=0.80-0.88). CONCLUSIONS: Sleep deprivation negatively affected recovery following a rugby league match, specifically impairing CMJ distance and cognitive function. Practitioners should promote adequate post-match sleep patterns or adjust training demands the next day to accommodate the altered physical and cognitive state following sleep deprivation.

The effect of sleep deprivation on BOLD activity elicited by a divided attention task

Sleep loss, widespread in today’s society and associated with a number of clinical conditions, has a detrimental effect on a variety of cognitive domains including attention. This study examined the sequelae of sleep deprivation upon BOLD fMRI activation during divided attention. Twelve healthy males completed two randomized sessions; one after 27 h of sleep deprivation and one after a normal night of sleep. During each session, BOLD fMRI was measured while subjects completed a cross-modal divided attention task (visual and auditory). After normal sleep, increased BOLD activation was observed bilaterally in the superior frontal gyrus and the inferior parietal lobe during divided attention performance. Subjects reported feeling significantly more sleepy in the sleep deprivation session, and there was a trend towards poorer divided attention task performance. Sleep deprivation led to a down regulation of activation in the left superior frontal gyrus, possibly reflecting an attenuation of top-down control mechanisms on the attentional system. These findings have implications for understanding the neural correlates of divided attention and the neurofunctional changes that occur in individuals who are sleep deprived.

Sleep deprivation and brain energy metabolism : in vivo studies in rats and humans

Sleep deprivation leads to increased subsequent sleep length and depth and to deficits in cognitive performance in humans. In animals extreme sleep deprivation is eventually fatal. The cellular and molecular mechanisms causing the symptoms of sleep deprivation are unclear. This thesis was inspired by the hypothesis that during wakefulness brain energy stores would be depleted, and they would be replenished during sleep. The aim of this thesis was to elucidate the energy metabolic processes taking place in the brain during sleep deprivation. Endogenous brain energy metabolite levels were assessed in vivo in rats and in humans in four separate studies (Studies I-IV). In the first part (Study I) the effects of local energy depletion on brain energy metabolism and sleep were studied in rats with the use of in vivo microdialysis combined with high performance liquid chromatography. Energy depletion induced by 2,4-dinitrophenol infusion into the basal forebrain was comparable to the effects of sleep deprivation: both increased extracellular concentrations of adenosine, lactate, and pyruvate, and elevated subsequent sleep. This result supports the hypothesis of a connection between brain energy metabolism and sleep. The second part involved healthy human subjects (Studies II-IV). Study II aimed to assess the feasibility of applying proton magnetic resonance spectroscopy (1H MRS) to study brain lactate levels during cognitive stimulation. Cognitive stimulation induced an increase in lactate levels in the left inferior frontal gyrus, showing that metabolic imaging of neuronal activity related to cognition is possible with 1H MRS. Study III examined the effects of sleep deprivation and aging on the brain lactate response to cognitive stimulation. No physiologic, cognitive stimulation-induced lactate response appeared in the sleep-deprived and in the aging subjects, which can be interpreted as a sign of malfunctioning of brain energy metabolism. This malfunctioning may contribute to the functional impairment of the frontal cortex both during aging and sleep deprivation. Finally (Study IV), 1H MRS major metabolite levels in the occipital cortex were assessed during sleep deprivation and during photic stimulation. N-acetyl-aspartate (NAA/H2O) decreased during sleep deprivation, supporting the hypothesis of sleep deprivation-induced disturbance in brain energy metabolism. Choline containing compounds (Cho/H2O) decreased during sleep deprivation and recovered to alert levels during photic stimulation, pointing towards changes in membrane metabolism, and giving support to earlier observations of altered brain response to stimulation during sleep deprivation. Based on these findings, it can be concluded that sleep deprivation alters brain energy metabolism. However, the effects of sleep deprivation on brain energy metabolism may vary from one brain area to another. Although an effect of sleep deprivation might not in all cases be detectable in the non-stimulated baseline state, a challenge imposed by cognitive or photic stimulation can reveal significant changes. It can be hypothesized that brain energy metabolism during sleep deprivation is more vulnerable than in the alert state. Changes in brain energy metabolism may participate in the homeostatic regulation of sleep and contribute to the deficits in cognitive performance during sleep deprivation.