Vigilance on the civil flight deck: incidence of sleepiness and sleep during long-haul flights and associated changes in physiological parameters

Relationship between sleep quality and gravitational Tolerance

BACKGROUND

The purpose of this study was to investigate the relationship between sleep quality and gravitational tolerance because sleep could directly affect physiological variables of the human body.

METHODS

For the present study, 157 male Korea Air Force Academy cadets were recruited. They were assigned into a gravity (G)-tolerance test pass group (GP, n = 87) and a G-tolerance test fail group (GF, n = 70). All participants were assessed for G-tolerance test and Pittsburgh Sleep Quality Index (PSQI), a self-report questionnaire. Physical fitness test was performed based on the physical fitness test of the Ministry of National Defense of Korea.

RESULTS

Independent t-test showed that PSQI global score (p < 0.001), PSQI sleep quality (p < 0.001), PSQI sleep onset latency (p = 0.009), PSQI sleep disturbance (p < 0.001), and PSQI daytime dysfunction (p < 0.001) were significantly different between the two groups. Participants with PSQI score less than 5 were more likely to have a longer G-tolerance test time (OR = 4.705, 95% CI = 2.00-11.05). Additionally, associations between those with PSQI score less than 5 (OR = 4.567, 95% CI = 1.94-10.74) were after adjusting (< 30 s and ≥ 30 s) for covariates. A negative correlation was found between G-tolerance test time and PSQI global score (p < 0.001). Negative correlations were found among 3 km running, push-up (p < 0.001), and sit-up (p < 0.001). A positive correlation was found between push-up and sit-up (p < 0.001).

CONCLUSION

In conclusion, participants with good sleep quality were 4.705 times more likely to have longer G-tolerance test time. Thus, it is important for aircraft pilots to manage their sleep quality. Pre-pilots should also improve their sleep quality to pass the G-tolerance test.

Psychophysiology of Monotonous Driving, Fatigue and Sleepiness in Train and Non-Professional Drivers: Driver Safety Implications

Fatigue and sleepiness are complex bodily states associated with monotony as well as physical and cognitive impairment, accidents, injury, and illness. Moreover, these states are often characteristic of professional driving. However, most existing work has focused on motor vehicle drivers, and research examining train drivers remains limited. As such, the present study psychophysiologically examined monotonous driving, fatigue, and sleepiness in a group of passenger train drivers and a group of non-professional drivers. Sixty-three train drivers and thirty non-professional drivers participated in the present study, which captured 32-lead electroencephalogram (EEG) data during a monotonous driving task. Fatigue and sleepiness were self-evaluated using the Pittsburgh Sleep Quality Index, the Epworth Sleepiness Scale, the Karolinksa Sleepiness Scale, and the Checklist of Individual Strength. Unexpectedly, fatigue and sleepiness scores did not significantly differ between the groups; however, train drivers generally scored lower than non-professional drivers, which may be indicative of individual and/or industry attempts to reduce fatigue. Across both groups, fatigue and sleepiness scores were negatively correlated with theta, alpha, and beta EEG variables clustered towards the fronto-central and temporal regions. Broadly, these associations may reflect a monotony-associated blunting of neural activity that is associated with a self-reported fatigue state.

Aviation and neurophysiology: A systematic review

This paper systematically reviews 20 years of publications (N = 54) on aviation and neurophysiology. The main goal is to provide an account of neurophysiological changes associated with flight training with the aim of identifying neurometrics indicative of pilot's flight training level and task relevant mental states, as well as to capture the current state-of-art of (neuro)ergonomic design and practice in flight training. We identified multiple candidate neurometrics of training progress and workload, such as frontal theta power, the EEG Engagement Index and the Cognitive Stability Index. Furthermore, we discovered that several types of classifiers could be used to accurately detect mental states, such as the detection of drowsiness and mental fatigue. The paper advances practical guidelines on terminology usage, simulator fidelity, and multimodality, as well as future research ideas including the potential of Virtual Reality flight simulations for training, and a brain-computer interface for flight training.

Forecasting crew fatigue risk on international flights under different policies in China during the COVID-19 outbreak

To predict the risk of fatigue for flight crews on international flights under the new operating model policy of the civil aviation exemption approach policy during the COVID-19 outbreak, and to provide scientific validation methods and ideas for the exemption approach policy. This paper uses the change in flight crew alertness as a validation indicator, and then constructs an alertness assessment model to predict flight crew fatigue risk based on the SAFTE model theory. Then, the corresponding in-flight rotation plans for the flight is designed according to the exemption approach policy issued by the CAAC, the CCAR-121 part policy and the real operational requirements of the airline, respectively, and finally the simulation results is compared by comparing the pilot alertness and cockpit crew alertness under the exemption approach policy and the CCAR-121 part policy with the flight duration. The results show that the flight crew alertness level for the flight in-flight rotation plan simulation designed under the exemption approach policy is higher or closer to the pilot alertness level for operational flights under the CCAR-121 Part policy. This validates the reasonableness and safety of the exemption approach policy issued by the CAAC to meet the requirements of epidemic prevention and control, and provides scientific support and solutions for fatigue monitoring and management.

Disturbance of the Circadian System in Shift Work and Its Health Impact

The various non-standard schedules required of shift workers force abrupt changes in the timing of sleep and light-dark exposure. These changes result in disturbances of the endogenous circadian system and its misalignment with the environment. Simulated night-shift experiments and field-based studies with shift workers both indicate that the circadian system is resistant to adaptation from a day- to a night-oriented schedule, as determined by a lack of substantial phase shifts over multiple days in centrally controlled rhythms, such as those of melatonin and cortisol. There is evidence that disruption of the circadian system caused by night-shift work results not only in a misalignment between the circadian system and the external light-dark cycle, but also in a state of internal desynchronization between various levels of the circadian system. This is the case between rhythms controlled by the central circadian pacemaker and clock genes expression in tissues such as peripheral blood mononuclear cells, hair follicle cells, and oral mucosa cells. The disruptive effects of atypical work schedules extend beyond the expression profile of canonical circadian clock genes and affects other transcripts of the human genome. In general, after several days of living at night, most rhythmic transcripts in the human genome remain adjusted to a day-oriented schedule, with dampened group amplitudes. In contrast to circadian clock genes and rhythmic transcripts, metabolomics studies revealed that most metabolites shift by several hours when working nights, thus leading to their misalignment with the circadian system. Altogether, these circadian and sleep-wake disturbances emphasize the all-encompassing impact of night-shift work, and can contribute to the increased risk of various medical conditions. Here, we review the latest scientific evidence regarding the effects of atypical work schedules on the circadian system, sleep and alertness of shift-working populations, and discuss their potential clinical impacts.

Exposure to hypoxia impairs helicopter pilots' awareness of environment

The purpose of the present study was to determine how hypoxia effects awareness of environment (AoE) in helicopter pilots operating at high altitude. Eight helicopter crews flew two operational flights in a flight simulator while breathing gas mixtures of 20.9% (equivalent to 0 m altitude) and 11.4% (equivalent to 4572 m or 15,000 ft altitude) oxygen in a single blinded, counterbalanced, repeated measures study. Each flight included five missions, during which environment items were introduced that the crews needed to be aware of, and respond to. In the 4572 m simulation, the crews missed overall 28 AoE items compared to 12 in the 0 m simulation (Z = -1.992; p = .046). In contrast, the crews' technical skills were not significantly effected by hypoxia. Remarkably, the majority of pilots did not notice they were hypoxic or recognise their hypoxia symptoms during the simulation flight at 4572 m. Practitioner summary We show that hypoxia has a detrimental effect on helicopter pilot's AoE and alertness. This can lead to an increased risk for flight safety. To mitigate this risk we recommend performing hypoxia training in a flight simulator, developing wearable systems for physiological monitoring of pilots and re-evaluating current altitude regulations. Abbreviations: ANOVA: Analysis of variance; AoE: awareness of environment; CSV: comma-separated values; HDU: helmet display unit; HR: heart rate; IQR: interquartile range; Mdn: median; NTS: non-technical skills; RNLAF: Royal Netherlands Air Force; PPM: parts per million; SpO2: oxygen saturation; SSS: Stanford sleepiness scale; TS: technical Skills.

Stimulant Use as a Fatigue Countermeasure in Aviation

INTRODUCTION: Fatigue is a common problem in aviation. The identification of efficacious fatigue countermeasures is crucial for sustaining flight performance during fatigue-inducing operations. Stimulants are not recommended for consistent use, but are often implemented during flight operations with a high risk of fatigue. As such, it is important to evaluate the efficacy of approved stimulants for sustaining flight performance, alertness, and mood.METHODS: Four electronic databases (PubMed, PsycInfo, SPORTDiscus, Web of Science) were systematically searched to identify research on the effects of caffeine, dextroamphetamine, and modafinil during simulated or in-flight operations.RESULTS: There were 12 studies identified that assessed the effects of at least 1 stimulant. Overall, dextroamphetamine and modafinil were effective for sustaining flight performance and pilot mood during extended wakefulness. Results with caffeine were inconsistent.DISCUSSION: Dextroamphetamine and modafinil appear to sustain flight performance and mood during extended wakefulness. However, most studies have used flight simulators and short operation durations. Additional research is needed in realistic settings and during longer duration operations. Caffeines effects were inconsistent across studies, possibly due to differences in study methodology or individual caffeine responses. Despite fatigue being a common problem in civilian aviation as well, only one study in this review included civil aviators. More research should be conducted on the effects of caffeine during civil operations.CONCLUSION: Dextroamphetamine and modafinil appear to be effective fatigue countermeasures but should be further evaluated in more ecologically valid settings. The effects of caffeine are unclear at this time and should continue to be evaluated.Ehlert AM, Wilson PB. Stimulant use as a fatigue countermeasure in aviation. Aerosp Med Hum Perform. 2021; 92(3):190200.

Neurophysiological adaptations to spaceflight and simulated microgravity

Changes in physiological functions after spaceflight and simulated spaceflight involve several mechanisms. Microgravity is one of them and it can be partially reproduced with models, such as head down bed rest (HDBR). Yet, only a few studies have investigated in detail the complexity of neurophysiological systems and their integration to maintain homeostasis. Central nervous system changes have been studied both in their structural and functional component with advanced techniques, such as functional magnetic resonance (fMRI), showing the main involvement of the cerebellum, cortical sensorimotor, and somatosensory areas, as well as vestibular-related pathways. Analysis of electroencephalography (EEG) led to contrasting results, mainly due to the different factors affecting brain activity. The study of corticospinal excitability may enable a deeper understanding of countermeasures' effect, since greater excitability has been shown being correlated with better preservation of functions. Less is known about somatosensory evoked potentials and peripheral nerve function, yet they may be involved in a homeostatic mechanism fundamental to thermoregulation. Extending the knowledge of such alterations during simulated microgravity may be useful not only for space exploration, but for its application in clinical conditions and for life on Earth, as well.

Electro-Encephalography and Electro-Oculography in Aeronautics: A Review Over the Last Decade (2010-2020)

Electro-encephalography (EEG) and electro-oculography (EOG) are methods of electrophysiological monitoring that have potentially fruitful applications in neuroscience, clinical exploration, the aeronautical industry, and other sectors. These methods are often the most straightforward way of evaluating brain oscillations and eye movements, as they use standard laboratory or mobile techniques. This review describes the potential of EEG and EOG systems and the application of these methods in aeronautics. For example, EEG and EOG signals can be used to design brain-computer interfaces (BCI) and to interpret brain activity, such as monitoring the mental state of a pilot in determining their workload. The main objectives of this review are to, (i) offer an in-depth review of literature on the basics of EEG and EOG and their application in aeronautics; (ii) to explore the methodology and trends of research in combined EEG-EOG studies over the last decade; and (iii) to provide methodological guidelines for beginners and experts when applying these methods in environments outside the laboratory, with a particular focus on human factors and aeronautics. The study used databases from scientific, clinical, and neural engineering fields. The review first introduces the characteristics and the application of both EEG and EOG in aeronautics, undertaking a large review of relevant literature, from early to more recent studies. We then built a novel taxonomy model that includes 150 combined EEG-EOG papers published in peer-reviewed scientific journals and conferences from January 2010 to March 2020. Several data elements were reviewed for each study (e.g., pre-processing, extracted features and performance metrics), which were then examined to uncover trends in aeronautics and summarize interesting methods from this important body of literature. Finally, the review considers the advantages and limitations of these methods as well as future challenges.

Assessment of Driver's Drowsiness Based on Fractal Dimensional Analysis of Sitting and Back Pressure Measurements

The most effective way of preventing motor vehicle accidents caused by drowsy driving is through a better understanding of drowsiness itself. Prior research on the detection of symptoms of drowsy driving has offered insights on providing drivers with advance warning of an elevated risk of crash. The present study measured back and sitting pressures during a simulated driving task under both high and low arousal conditions. Fluctuation of time series of center of pressure (COP) movement of back and sitting pressure was observed to possess a fractal property. The fractal dimensions were calculated to compare the high and low arousal conditions. The results showed that under low arousal (the drowsiness state) the fractal dimension was significantly lower than what was calculated with high arousal. Accumulated drowsiness thus contributed to the loss of self-similarity and unpredictability of time series of back and sitting pressure measurement. Drowsiness further reduces the complexity of the posture control system as viewed from back and sitting pressure. Thus, fractal dimension is a necessary and sufficient condition of a decreased arousal level. It further is a necessary condition for detecting the interval or point in time with high risk of crash.

Electroencephalography as a predictor of self-report fatigue/sleepiness during monotonous driving in train drivers

OBJECTIVE

In this study, electroencephalography activity recorded during monotonous driving was investigated to examine the predictive capability of monopolar EEG analysis for fatigue/sleepiness in a cohort of train drivers.

APPROACH

Sixty-three train drivers participated in the study, where 32- lead monopolar EEG data was recorded during a monotonous driving task. Participant sleepiness was assessed using the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the Karolinksa sleepiness scale (KSS) and the checklist of individual strength 20 (CIS20).

MAIN RESULTS

Self-reported fatigue/sleepiness scores of the train driver cohort were primarily associated with EEG delta, theta, and alpha variables; however, some beta and gamma associations were also implicated. Furthermore, general linear models informed by these EEG variables were able to predict self-reported scores with varying degrees of success, representing between 48% and 54% of variance in fatigue scores.

SIGNIFICANCE

Self-reported fatigue/sleepiness scores of train drivers were predicted with varying degrees of success (dependent upon the self-reported fatigue/sleepiness measure) by alterations to monopolar delta, theta, and alpha band activity variables, indicating EEG as a potential indicator for fatigue/sleepiness in train drivers.

Detecting Pilot's Engagement Using fNIRS Connectivity Features in an Automated vs. Manual Landing Scenario

Monitoring pilot's mental states is a relevant approach to mitigate human error and enhance human machine interaction. A promising brain imaging technique to perform such a continuous measure of human mental state under ecological settings is Functional Near-InfraRed Spectroscopy (fNIRS). However, to our knowledge no study has yet assessed the potential of fNIRS connectivity metrics as long as passive Brain Computer Interfaces (BCI) are concerned. Therefore, we designed an experimental scenario in a realistic simulator in which 12 pilots had to perform landings under two contrasted levels of engagement (manual vs. automated). The collected data were used to benchmark the performance of classical oxygenation features (i.e., Average, Peak, Variance, Skewness, Kurtosis, Area Under the Curve, and Slope) and connectivity features (i.e., Covariance, Pearson's, and Spearman's Correlation, Spectral Coherence, and Wavelet Coherence) to discriminate these two landing conditions. Classification performance was obtained by using a shrinkage Linear Discriminant Analysis (sLDA) and a stratified cross validation using each feature alone or by combining them. Our findings disclosed that the connectivity features performed significantly better than the classical concentration metrics with a higher accuracy for the wavelet coherence (average: 65.3/59.9 %, min: 45.3/45.0, max: 80.5/74.7 computed for HbO/HbR signals respectively). A maximum classification performance was obtained by combining the area under the curve with the wavelet coherence (average: 66.9/61.6 %, min: 57.3/44.8, max: 80.0/81.3 computed for HbO/HbR signals respectively). In a general manner all connectivity measures allowed an efficient classification when computed over HbO signals. Those promising results provide methodological cues for further implementation of fNIRS-based passive BCIs.

Working hours associated with unintentional sleep at work among airline pilots

OBJECTIVE

Tto identify factors associated with unintentional sleep at work of airline pilots.

METHODS

This is a cross-sectional epidemiological study conducted with 1,235 Brazilian airline pilots, who work national or international flights. Data collection has been performed online. We carried out a bivariate and multiple logistic regression analysis, having as dependent variable unintentional sleep at work. The independent variables were related to biodemographic data, characteristics of the work, lifestyle, and aspects of sleep.

RESULTS

The prevalence of unintentional sleep while flying the airplane was 57.8%. The factors associated with unintentional sleep at work were: flying for more than 65 hours a month, frequent technical delays, greater need for recovery after work, work ability below optimal, insufficient sleep, and excessive sleepiness.

CONCLUSIONS

The occurrence of unintentional sleep at work of airline pilots is associated with factors related to the organization of the work and health.

A method for predicting the risk of virtual crashes in a simulated driving task using behavioural and subjective drowsiness measures

This study proposed a procedure for predicting the point in time with high risk of virtual crash using a control chart methodology for behavioural measures during a simulated driving task. Tracking error, human back pressure, sitting pressure and horizontal and vertical neck bending angles were measured during the simulated driving task. The time with a high risk of a virtual crash occurred in 9 out of 10 participants. The time interval between the successfully detected point in time with high risk of virtual crash and the point in time of virtual crash ranged from 80 to 324 s. The proposed procedure for predicting the point in time with a high risk of a crash is promising for warning drivers of the state of high risk of crash. Practitioner Summary: Many fatal crashes occur due to drowsy driving. We proposed a method to predict the point in time with high risk of virtual crash before such a virtual crash occurs. This is done using behavioural measures during a simulated driving task. The effectiveness of the method is also demonstrated.

Benefits of Sleep Extension on Sustained Attention and Sleep Pressure Before and During Total Sleep Deprivation and Recovery

OBJECTIVES

To investigate the effects of 6 nights of sleep extension on sustained attention and sleep pressure before and during total sleep deprivation and after a subsequent recovery sleep.

DESIGN

Subjects participated in two experimental conditions (randomized cross-over design): extended sleep (EXT, 9.8 ± 0.1 h (mean ± SE) time in bed) and habitual sleep (HAB, 8.2 ± 0.1 h time in bed). In each condition, subjects performed two consecutive phases: (1) 6 nights of either EXT or HAB (2) three days in-laboratory: baseline, total sleep deprivation and after 10 h of recovery sleep.

SETTING

Residential sleep extension and sleep performance laboratory (continuous polysomnographic recording).

PARTICIPANTS

14 healthy men (age range: 26-37 years).

INTERVENTIONS

EXT vs. HAB sleep durations prior to total sleep deprivation.

MEASUREMENTS AND RESULTS

Total sleep time and duration of all sleep stages during the 6 nights were significantly higher in EXT than HAB. EXT improved psychomotor vigilance task performance (PVT, both fewer lapses and faster speed) and reduced sleep pressure as evidenced by longer multiple sleep latencies (MSLT) at baseline compared to HAB. EXT limited PVT lapses and the number of involuntary microsleeps during total sleep deprivation. Differences in PVT lapses and speed and MSLT at baseline were maintained after one night of recovery sleep.

CONCLUSION

Six nights of extended sleep improve sustained attention and reduce sleep pressure. Sleep extension also protects against psychomotor vigilance task lapses and microsleep degradation during total sleep deprivation. These beneficial effects persist after one night of recovery sleep.

The Effects of the Level of Alertness During the Rest Period on Subsequent Performance

The aim of this study was to examine how to take an effective rest to prevent a decline in alertness at work. The relationship between alertness during the rest period and subsequent task performance were investigated. The electroencephalogram (EEG) during the rest period was classified into 3 types, and these types had a significant effect on performance after the rest period. Type 1 (increasing in theta, alpha 2, and beta 1 power) was the best one for carrying out the task, whereas performance gradually declined in Type 3 (no change in EEG activity). In the case of Type 1, the method that would relieve sleep inertia had a more positive impact on performance after the rest period.

In-flight automatic detection of vigilance states using a single EEG channel

Sleepiness and fatigue can reach particularly high levels during long-haul overnight flights. Under these conditions, voluntary or even involuntary sleep periods may occur, increasing the risk of accidents. The aim of this study was to assess the performance of an in-flight automatic detection system of low-vigilance states using a single electroencephalogram channel. Fourteen healthy pilots voluntarily wore a miniaturized brain electrical activity recording device during long-haul flights ( 10 ±2.0 h, Atlantic 2 and Falcon 50 M, French naval aviation). No subject was disturbed by the equipment. Seven pilots experienced at least a period of voluntary ( 26.8 ±8.0 min, n = 4) or involuntary sleep (N1 sleep stage, 26.6 ±18.7 s, n = 7) during the flight. Automatic classification (wake/sleep) by the algorithm was made for 10-s epochs (O1-M2 or C3-M2 channel), based on comparison of means to detect changes in α, β, and θ relative power, or ratio [( α+θ)/β], or fuzzy logic fusion (α, β). Pertinence and prognostic of the algorithm were determined using epoch-by-epoch comparison with visual-scoring (two blinded readers, AASM rules). The best concordance between automatic detection and visual-scoring was observed within the O1-M2 channel, using the ratio [( α+θ )/β] ( 98.3 ±4.1% of good detection, K = 0.94 ±0.07, with a 0.04 ±0.04 false positive rate and a 0.87 ±0.10 true positive rate). Our results confirm the efficiency of a miniaturized single electroencephalographic channel recording device, associated with an automatic detection algorithm, in order to detect low-vigilance states during real flights.

Losing the struggle to stay awake: divergent thalamic and cortical activity during microsleeps

Maintaining alertness is critical for safe and successful performance of most human activities. Consequently, microsleeps during continuous visuomotor tasks, such as driving, can be very serious, not only disrupting performance but sometimes leading to injury or death due to accidents. We have investigated the neural activity underlying behavioral microsleeps--brief (0.5-15 s) episodes of complete failure to respond accompanied by slow eye-closures--and EEG theta activity during drowsiness in a continuous task. Twenty healthy normally-rested participants performed a 50-min continuous tracking task while fMRI, EEG, eye-video, and responses were simultaneously recorded. Visual rating of performance and eye-video revealed that 70% of the participants had frequent microsleeps. fMRI analysis revealed a transient decrease in thalamic, posterior cingulate, and occipital cortex activity and an increase in frontal, posterior parietal, and parahippocampal activity during microsleeps. The transient activity was modulated by the duration of the microsleep. In subjects with frequent microsleeps, power in the post-central EEG theta was positively correlated with the BOLD signal in the thalamus, basal forebrain, and visual, posterior parietal, and prefrontal cortices. These results provide evidence for distinct neural changes associated with microsleeps and with EEG theta activity during drowsiness in a continuous task. They also suggest that the occurrence of microsleeps during an active task is not a global deactivation process but involves localized activation of fronto-parietal cortex, which, despite a transient loss of arousal, may constitute a mechanism by which these regions try to restore responsiveness.

Algorithm for automatic analysis of electro-oculographic data

BACKGROUND

Large amounts of electro-oculographic (EOG) data, recorded during electroencephalographic (EEG) measurements, go underutilized. We present an automatic, auto-calibrating algorithm that allows efficient analysis of such data sets.

METHODS

The auto-calibration is based on automatic threshold value estimation. Amplitude threshold values for saccades and blinks are determined based on features in the recorded signal. The performance of the developed algorithm was tested by analyzing 4854 saccades and 213 blinks recorded in two different conditions: a task where the eye movements were controlled (saccade task) and a task with free viewing (multitask). The results were compared with results from a video-oculography (VOG) device and manually scored blinks.

RESULTS

The algorithm achieved 93% detection sensitivity for blinks with 4% false positive rate. The detection sensitivity for horizontal saccades was between 98% and 100%, and for oblique saccades between 95% and 100%. The classification sensitivity for horizontal and large oblique saccades (10 deg) was larger than 89%, and for vertical saccades larger than 82%. The duration and peak velocities of the detected horizontal saccades were similar to those in the literature. In the multitask measurement the detection sensitivity for saccades was 97% with a 6% false positive rate.

CONCLUSION

The developed algorithm enables reliable analysis of EOG data recorded both during EEG and as a separate metrics.

Fatigue in aviation

Pilot fatigue is a significant, but often under-reported problem in both civilian and military aviation operations. Although estimates vary, official statistics indicate that fatigue is involved in at least 4-8% of aviation mishaps, and surveys of pilots and aircrew members reveal that fatigue is an important concern throughout today's 24/7 flight operations. Regulatory efforts aimed at limiting flight hours and ensuring at least minimal periods of crew rest have to some extent mitigated fatigue-related difficulties in the cockpit, but it is clear that much remains to be done about this insidious threat to air safety. Scheduling factors, sleep deprivation, circadian disruptions, and extended duty periods continue to challenge the alertness and performance levels of both short-haul and long-haul pilots and crews. Solutions for these problems are not straightforward, but they can be developed through the cooperative efforts of scientists, regulators, managers, and the pilots themselves. Over the past 20 years, scientific understanding of human sleep, fatigue, and circadian rhythms has expanded considerably. The thorough integration of this new knowledge into modern crew-resource management practices will facilitate the establishment of optimal crew scheduling routines and the implementation of valid aviation fatigue countermeasures.

Drowsiness detection by thoracic effort signal analysis in real driving environments

Detection of drowsiness while driving is a leading objective in advanced driver assistance systems. This work presents a new index to assess the alertness state of drivers based on the respiratory dynamics derived from an inductive band. More than 100 hours of driving in real environments from 13 healthy subjects were analyzed. The proposed method has a sensitivity of 93.7% and specificity of 86.3% in detecting full awake drivers while it has a sensitivity of 83.1% and specificity of 95.3% in detecting drowsy drivers. The results show that the proposed index may be promising to assess the alertness state of real drivers.

Fatigue and extended work hours among cardiovascular perfusionists: 2010 Survey

Due to the emergent unpredictable nature of cardiac surgery, perfusionists, potentially, are susceptible to extended work hours and acute sleep deprivation. While fatigue among other healthcare clinicians has been studied, there has been no research on this topic specifically in the perfusion community. Therefore, the purpose of this study was to: (1) collect preliminary data on the prevalence of fatigue in perfusion and (2) identify if there were concerns regarding fatigue, performance and perfusion safety.

In May 2010, a link to a 50-question survey ( surveymonkey.com ) was posted on Perflist and Perfmail. The survey was closed in July 2010. There were 445 respondents and data were analyzed and expressed as a response percent.

Participants included 27% chief perfusionists/managers, 67% staff perfusionists, and 6.0% other (perfusion education faculty, retired perfusionists, locum tenens). Regarding extended work hours, 68.9% of surveyed perfusionists have worked at the hospital for greater than 23 hours straight and 17.5% have worked continuously for over 36 hours. Actual performance of cardiopulmonary bypass (CPB) after 17, 23, and 36 hours of wakefulness was reported by 82.9%, 63% and 14.8% respondents, respectively. Regarding bathroom requirements while on CPB, 87.5% have felt extremely uncomfortable at least once, 19.9% have relieved themselves in the operating room at least once, and 22.3% have left the pump attended by a non-perfusionist to use the restroom at least once. Microsleep during CPB was reported by 49.5% of respondents. Automobile accidents attributed to an extended period of work and fatigue was reported by 6.9% and another 44.4% reported a near-miss auto accident. A fatigue-related minor error was reported by 66% and 6.7% admit to having a serious perfusion accident believed to be due to fatigue. Concerning critical phases of bypass, 51.5% believe that they perform less effectively when fatigued. Additionally, 75.9% indicate that they have been concerned about their ability to perform their job adequately due to fatigue-related acute sleep deprivation. Opinions regarding workplace management were as follows; 48% believe that fatigue can play a role in our profession and managers should do what they can to provide a rested staff, but, unfortunately, it is impractical to set work limits; 32.2% believe fatigue issues should be taken more seriously and specific guidelines should be stated by our professional organizations and 13.4% believe that limits should be established, legislated, and enforced by state or federal authorities.

Based upon this preliminary survey data, it appears that fatigue and acute sleep deprivation is a significant safety concern in the perfusion community. Further research must be performed to understand actual performance degradation that may occur in fatigued perfusionists performing CPB.

Slow eye movement as a possible predictor of reaction delays to auditory warning alarms in a drowsy state

In recently developed intelligent vehicles, warning alarms are often used to prompt avoidance behaviours from drivers facing imminent hazardous situations. However, when critical reaction delays to auditory stimulation are anticipated, the alarm should be activated earlier to compensate for such delays. It was found that reaction times to an auditory stimulus significantly increased in the presence of slow eye movement (SEM), which is known to occur frequently during the wake-sleep transition. The reaction delay could not be attributed to temporal effects such as fatigue and was invariant regardless of response effectors (finger or foot). Moreover, it was found that applied pedal force decreased immediately after an auditory stimulus interrupted SEM. Consequently, it was concluded that SEM can be a good predictor of reaction delays to auditory warning alarms when drivers are in a drowsy state. STATEMENT OF RELEVANCE: The present study demonstrated that simple auditory reaction time significantly increased when SEM emerged. In the design of vehicle safety systems using warning alarms to prompt avoidance behaviours from drivers, such reaction delays during SEM must be taken into account.

How well do pilots sleep during long-haul flights?

It is imperative that shiftworkers in safety-critical workplaces obtain sufficient sleep to operate effectively. This presents a challenge to long-haul airline pilots who are required to supplement normal bed sleep with sleep on-board an aircraft during flight. In the current study, the sleep/wake behaviour of 301 airline pilots operating long-haul flight patterns was monitored for at least 2 weeks using self-report sleep diaries and wrist activity monitors. The data indicate that sleep opportunities in on-board rest facilities during long-haul flights result in a similar amount of sleep, but only 70% as much recovery, as duration-matched bed sleeps. STATEMENT OF RELEVANCE: This study indicates that in-flight sleep provides airline pilots with 70% as much restoration as duration-matched bed sleep. To increase the restoration provided by in-flight sleep, airlines could take measures to improve the quality, or increase the amount, of sleep obtained by pilots during flights.

Combining electrodermal responses and cardiovascular measures for probing adaptive automation during simulated flight

Adaptive automation increases the operator's workload in case of hypovigilance and takes over more responsibility if workload becomes too high. Two consecutive studies were conducted to construct a biocybernetic adaptive system for a professional flight simulator, based on autonomic measures. Workload was varied through different stages of turbulences. In a first study with 18 participants, electrodermal responses of experimental subjects oscillated very close to the individual set point, demonstrating that workload level was adjusted as a result of adaptive control, which was not the case in yoked control subjects without adaptive automation. Combining electrodermal responses with heart rate variability in a second study with 48 participants further enhanced the adaptive power which was seen in even smaller set point deviations for the experimental compared to the yoked control group. We conclude that the level of arousal can be adjusted to avoid hypovigilance by combining autonomic measures in a closed loop.

Acoustic sleepiness detection: framework and validation of a speech-adapted pattern recognition approach

This article describes a general framework for detecting sleepiness states on the basis of prosody, articulation, and speech-quality-related speech characteristics. The advantages of this automatic real-time approach are that obtaining speech data is nonobstrusive and is free from sensor application and calibration efforts. Different types of acoustic features derived from speech, speaker, and emotion recognition were employed (frame-level-based speech features). Combing these features with high-level contour descriptors, which capture the temporal information of frame-level descriptor contours, results in 45,088 features per speech sample. In general, the measurement process follows the speech-adapted steps of pattern recognition: (1) recording speech, (2) preprocessing, (3) feature computation (using perceptual and signal-processing-related features such as, e.g., fundamental frequency, intensity, pause patterns, formants, and cepstral coefficients), (4) dimensionality reduction, (5) classification, and (6) evaluation. After a correlation-filter-based feature subset selection employed on the feature space in order to find most relevant features, different classification models were trained. The best model-namely, the support-vector machine-achieved 86.1% classification accuracy in predicting sleepiness in a sleep deprivation study (two-class problem, N=12; 01.00-08.00 a.m.).

The Sleep, Subjective Fatigue, and Sustained Attention of Commercial Airline Pilots during an International Pattern

International commercial airline pilots may experience heightened fatigue due to irregular sleep schedules, long duty days, night flying, and multiple time zone changes. Importantly, current commercial airline flight and duty time regulations are based on work/rest factors and not sleep/wake factors. Consequently, the primary aim of the current study was to investigate pilots' amount of sleep, subjective fatigue, and sustained attention before and after international flights. A secondary aim was to determine whether prior sleep and/or duty history predicted pilots' subjective fatigue and sustained attention during the international flights. Nineteen pilots (ten captains, nine first officers; mean age: 47.42+/-7.52 years) participated. Pilots wore wrist activity monitors and completed sleep and duty diaries during a return pattern from Australia to Europe via Asia. The pattern included four flights: Australia-Asia, Asia-Europe, Europe-Asia, and Asia-Australia. Before and after each flight, pilots completed a 5 min PalmPilot-based psychomotor vigilance task (PVT) and self-rated their level of fatigue using the Samn-Perelli Fatigue Checklist. Separate repeated-measures ANOVAs were used to determine the impact of stage of flight and flight sector on the pilots' sleep in the prior 24 h, self-rated fatigue, and PVT mean response speed. Linear mixed model regression analyses were conducted to examine the impact of sleep in the prior 24 h, prior wake, duty length, and flight sector on pilots' self-rated fatigue and sustained attention before and after the international flights. A significant main effect of stage of flight was found for sleep in the prior 24 h, self-rated fatigue, and mean response speed (all p < 0.05). In addition, a significant main effect of flight sector on self-rated fatigue was found (p < .01). The interaction between flight sector and stage of flight was significant for sleep in the prior 24 h and self-rated fatigue (both p < .05). Linear mixed model analyses indicated that sleep in the prior 24 h was a significant predictor of self-rated fatigue and mean response speed after the international flight sectors. Flight sector was also a significant predictor of self-rated fatigue. These findings highlight the importance of sleep and fatigue countermeasures during international patterns. Furthermore, in order to minimize the risk of fatigue, the sleep obtained by pilots should be taken into account in the development of flight and duty time regulations.

Effects of loratadine/montelukast on vigilance and alertness task performance in a simulated cabin environment

INTRODUCTION

Sedating effects of some medications used to treat allergic rhinitis (AR) symptoms can impair an individual's ability to function optimally. The objective of this study was to characterize the effects of a single dose of loratadine/montelukast (L/M) versus placebo and diphenhydramine on daytime somnolence and psychomotor performance in healthy volunteers.

METHODS

In this single-center, randomized, double-blind, placebo- and active-controlled,three-way crossover study, healthy volunteers received single doses of placebo, L/M 10 mg/10 mg, and diphenhydramine 50 mg. Subjects (n=23) were evaluated under simulated cabin pressure using the following tools: Vigilance and Tracking Task (VigTrack), measuring vigilance and tracking performance; the Multi-Attribute Task Battery (MAT), measuring ability to perform multiple tasks simultaneously; and the Stanford Sleepiness Scale (SSS), measuring sedative effects of medication, at baseline and each hour from 1 to 6 hours postdose. Safety was monitored via adverse events and vital signs.

RESULTS

Performances on VigTrack and MAT from 1 to 6 hours after dosing were not significantly different between L/M and placebo groups; in contrast, diphenhydramine resulted in significant impairment of tracking for up to 5 hours (P< or =0.01) and vigilance performance for up to 3 hours (P< or =0.05) on VigTrack versus placebo. Scores of subjective sleepiness as measured by SSS were similar for patients treated with L/M versus placebo, whereas significant increases in sleepiness occurred between 1-5 hours posttreatment in diphenhydramine-treated patients versus placebo-treated patients (P< or =0.05).

CONCLUSIONS

L/M is similar to placebo in effects on daytime somnolence and psychomotor performance. L/M treatment resulted in significantly less sleepiness and impairment of vigilance and tracking than diphenhydramine.

Blinks and saccades as indicators of fatigue in sleepiness warnings: looking tired?

The present study examines changes in a variety of oculomotoric variables as a function of increasing sleepiness in 129 participants, who have been passed through a broad range of subjective alertness. Up to now, spontaneous eye blinks are the most promising biosignal for in-car sleepiness warnings. Reviewing the current literature on eye movements and fatigue, experimental data are provided including additional indicative oculomotoric parameters; inter-individual differences in the experiments were also assessed. Here, self-rated alertness decreased over six steps on average and proved itself a reliable measurement. Regarding oculomotoric parameters, blink duration, delay of lid reopening, blink interval and standardised lid closure speed were identified as the best indicators of subjective as well as objective sleepiness. Saccadic parameters and fixation durations also showed specific changes with increasing sleepiness. Substantial inter-individual differences in all of these variables were illustrated. Oculomotoric parameters were linked to three different components of sleepiness while driving: a) deactivation; b) decreasing attention, resulting in disinhibition of spontaneous blinks and reflexive saccades; c) increasing attempts of self-activation. Finally, implications for the development of drowsiness detection devices were discussed.

Alertness management strategies for operational contexts

This review addresses the problem of fatigue (on-the-job-sleepiness) attributable to sleep loss in modern society and the scientifically proven strategies useful for reducing fatigue-related risks. Fatigue has become pervasive because many people work non-standard schedules, and/or they consistently fail to obtain sufficient sleep. Sleep restriction, sleep deprivation, and circadian desynchronization produce a variety of decrements in cognitive performance as well as an array of occupational and health risks. A number of real-world mishaps have resulted from performance failures associated with operator sleepiness. In some cases, fatigue/sleepiness is unavoidable, at least temporarily, due to job-related or other factors, but in other cases, fatigue/sleepiness results from poor personal choices. Furthermore, some individuals are more vulnerable to the effects of sleep loss than others. Fortunately, fatigue-related risks can be mitigated with scientifically valid alertness-management strategies. Proper work/rest scheduling and good sleep hygiene are of primary importance. If sleep time is available but sleep is difficult to obtain, sleep-inducing medications and behavioral circadian-adjustment strategies are key. In fatiguing situations such as when sleep opportunities are temporarily inadequate, limiting time on tasks, strategic napping, and the potential use of alertness-enhancing compounds must be considered. To optimize any alertness-management program, everyone must first be educated about the nature of the problem and the manner in which accepted remedies should be implemented. In the near future, objective fatigue-detection technologies may contribute substantially to the alleviation of fatigue-related risks in real-world operations.

Sleepiness and head movements

Sleepiness in working life is critical and strongly associated to work related accidents. The relationship between sleepiness and head movements is poorly investigated. The pattern of head movements over time was investigated in a laboratory study with ten subjects either sleep-deprived or rested. Head movements were obtained by an inclinometer placed on the subject's forehead, and the recording was continuous. Results show that subjects when sleep-deprived moved their head more and had more extreme head movements compared to when rested. An increase of the velocity and the number of extreme head movements over time were noted when the subjects were sleep-deprived and when rested. The increase of head movements was more linear over time in the rested condition, whereas in sleep-deprived conditions most of the increase appeared during the first hour. No significant differences of between forward-backward movements and left-right movements could be found. When rested, the changes in head movements correlated with ratings of sleepiness, EEG activity, and heart rate variability. Head movements can be a used as an indicator of sleepiness.

Recovery after prolonged sleep deprivation: residual effects of slow-release caffeine on recovery sleep, sleepiness and cognitive functions

A long work schedule often results in sleep deprivation, sleepiness, impaired performance and fatigue. We investigated the residual effects of slow-release caffeine (SRC) on sleep, sleepiness and cognitive performance during a 42-hour recovery period following a 64-hour continuous wakefulness period in 16 healthy males, according to a double-blind, randomised, placebo-controlled, crossover study. Three hundred milligrams of SRC or placebo was given twice a day at 21:00 and 9:00 during the first 48 h of wakefulness. Recovery sleep was analysed with electroencephalography (EEG) and wrist actigraphy, daytime sleepiness with continuous EEG, sleep latency tests and actigraphy and cognitive functions with computerized tests from the NATO AGARD STRES battery. Both drug groups exhibited almost the same sleep architecture with a rebound of slow-wave sleep during both recovery nights and of REM sleep during the second night. Wakefulness level and cognitive functions were similarly impaired in both groups on the first day of recovery and partially returned to baseline on the second. To conclude, SRC appears to have no unwanted side-effects on recovery sleep, wakefulness and cognitive performance after a long period of sleep deprivation and might therefore be a useful choice over other psychostimulants for a long work schedule.

Eyelid movements measured by Nightcap predict slow eye movements during quiet wakefulness in humans

A precipitous decline in eyelid movements (ELMs) has been shown to be a highly reliable indicator of sleep onset. While ELMs correlate well with eye movements during waking and rapid eye movement (REM) sleep, the eye sensor remains silent during the period of slow eye movements (SEMs) typical of sleep onset. If the ELM density (e.g. ELMs per minute) dropped simultaneously with the appearance of SEMs prior to sleep onset, it could be a promising tool for identifying decreases in alertness prior to overt sleep onset. The present study was designed to determine whether the presence of SEMs in the transitional period preceding stage 1 sleep is reflected in decreases in ELM density. ELM densities were computed for 2.5-s epochs with and without SEMs, as well as for 15-s epochs. Decreases in ELM density not only were an excellent correlate of the appearance of SEMs during wakefulness with closed eyes, but also a good predictor of their occurrence (c. 82% accuracy) at a time resolution of 2.5 s. Based on these results, we conclude that ELM density reliably predicts moderate changes in the level of alertness during quiet wakefulness.

Daytime sleepiness and its evaluation

Basic models of sleepiness, focusing on the homeostatic and circadian components of sleepiness, are able to predict important fluctuations of sleepiness. However, they fail in explaining certain sleepiness phenomena, as for instance in insomnia patients. To meet this shortcoming, modern models incorporate the arousal component of sleepiness, in addition to the sleep drive. While these models mainly concentrate on short-term changes in sleepiness, "state" sleepiness, there are indications that a stable characteristic level of sleepiness, "trait" sleepiness, is also an important determinant of a person's level of sleepiness. This leads to a conceptualization of sleepiness in which situational factors modify a basal level of sleep drive and arousal. It implies that sleepiness is not a unitary concept and can reflect essentially different states. Multiple sleepiness assessment tools have been proposed in the past. The majority of them offer valuable information, but they do not grasp all aspects of sleepiness. We should bear in mind that tools for assessing sleepiness are always operationalizations reflecting the theoretical framework the investigator has on sleepiness. Hence, rather than searching for a gold standard for the measurement of sleepiness, future research effort should be aimed at linking the various measurement techniques with the hypothesized underlying components of sleepiness on a sound empirical basis.

Health in a 24-h society

With increasing economic and social demands, we are rapidly evolving into a 24-h society. In any urban economy, about 20% of the population are required to work outside the regular 0800-1700 h working day and this figure is likely to increase. Although the increase in shiftwork has led to greater flexibility in work schedules, the ability to provide goods and services throughout the day and night, and possibly greater employment opportunities, the negative effects of shiftwork and chronic sleep loss on health and productivity are now being appreciated. For example, sleepiness surpasses alcohol and drugs as the greatest identifiable and preventable cause of accidents in all modes of transport. Industrial accidents associated with night work are common, perhaps the most famous being Chernobyl, Three Mile Island, and Bhopal.