In-flight Sleep Research Articles

Effects of moderate alcohol consumption and hypobaric hypoxia: implications for passengers’ sleep, oxygen saturation and heart rate on long-haul flights

BackgroundPassengers on long-haul flights frequently consume alcohol. Inflight sleep exacerbates the fall in blood oxygen saturation (SpO2) caused by the decreased oxygen partial pressure in the cabin. We investigated the...

Managing the challenge of fatigue for pilots operating ultra-long range flights

IntroductionUltra-long range (ULR) flights are defined as exceeding regulatory limits: normally 16 h flight time. They pose challenges due to long duty periods that could result in extended wakefulness and sleep loss, increasing the risk of fatigue. This study describes the mitigations used to manage fatigue in these operations. Two data collection phases were conducted on the Auckland-Chicago ULR route: when the route commenced (Study 1) and when the flight crew complement was altered (Study 2). Seasonal differences were also investigated.MethodsStudy 1 involved 72 crew who completed diaries and wore an actigraph to record sleep pre-departure, throughout the trip, and on return. In-flight, fatigue, sleepiness and workload were reported, and reaction time performance was measured. Study 2 involved 75 crew and data collection in the northern summer and northern winter. Crew completed diaries throughout the trip.ResultsStudy 1 data found crew sleep longer than usual in the 24 h pre trip and post flights. On the shorter outbound flight in-flight sleep averaged 3.3 h and on the longer inbound flight, 3.3–3.8 h, with most crew taking 3 breaks. Ratings of sleepiness and fatigue increased, and reaction time performance declined across flights, with greater decrements on longer inbound flights. Pilots did not fully adjust their sleep patterns to local time during the layover and no seasonal differences were found. Comparisons between Study 1 and 2 showed no difference in ratings of fatigue and sleepiness or in-flight sleep duration with an altered crew complement. There was a trend for Captains to report greater workload and less in-flight sleep in Study 2.DiscussionMitigations that allow for preparation and recovery are well utilized by crew. In-flight sleep is relatively short and ways of increasing the amount of sleep obtained should be considered. The incomplete adaptation of sleep during the layover has implications for rest break strategies on the return flight. The altered crew complement did not result in higher levels of fatigue or sleepiness or less in-flight sleep on average, although findings suggest a need to understand the effects of changing the crew complement on workload and in-flight sleep for Captains.

Managing cabin crew fatigue during ultra-long range operations

IntroductionUltra-long range (ULR) flights have the potential to increase fatigue-related risk for cabin crew, if the extended flight times are associated with extended wakefulness, sleep loss and higher levels of crew fatigue. ULR flights may also require longer opportunities for recovery sleep. This study evaluates the utilization of fatigue risk mitigations for cabin crew operating the Auckland – Chicago ULR route with a two-day layover.Methods65 cabin crew (45 women; aged 20–59 years) wore an actigraph and completed a sleep/duty diary for 3 local nights prior to, throughout, and for 3 local nights after a ULR trip. Crewmembers rated their fatigue (Samn-Perelli Crew Status Check), sleepiness (Karolinska Sleepiness Scale), and workload (OW; NASA-TLX) at key times during each flight. Jet lag was rated each day at home and during layover.ResultsFatigue and sleepiness were highest at top-of-descent and after landing and were higher on the inbound flight than on the outbound flight. For every hour of additional sleep in-flight, top-of-descent fatigue ratings decreased by 0.24 points and top-of-descent sleepiness ratings decreased by 0.38, whereas top-of-descent fatigue and sleepiness ratings increased by 0.24 points with every 10-point increase in OW ratings. Crew slept more in the 24-hours prior to the outbound (M = 8.5 h) and inbound flights (M = 9.1 h) compared to pre-trip baseline days (M = 8.2 h). Post-trip, crew slept more during the first day (M = 9.9 h) compared to baseline, with 95% taking a daytime nap. Jet lag ratings decreased daily on return home but were still higher on the fourth day than on the day of the outbound flight.DiscussionCabin crew prepare for ULR flights by obtaining more sleep prior to departure. However, large individual differences in sleep and declining jet lag ratings across pre-trip days suggest that some crewmembers may still be recovering from a previous trip. Further refinement of in-flight sleep strategies and workload mitigations could be considered for managing fatigue risk at top-of-descent. Findings also highlight the importance of a protected period of post-trip rest to facilitate cabin crews' recovery from the effects of sleep restriction and circadian disruption associated with this ULR trip.

Prevalence of sleep disorders in a large French cohort of aircrew members and risk of in-flight sleepiness

Background/objectives: Sleep disorders are a critical issue for flight safety. Previous studies have shown a high prevalence of sleep disorders and excessive sleepiness in the general population and some aircrews. The objectives of this study are to measure the prevalence of excessive daytime sleepiness and sleep disorders in aircrews, and to determine the risk factors of falling asleep during a flight. Methodsthis is a monocentric study based on questionnaires, including all professional civilian and military aircrews examined in an aeromedical center between January and May 2021. The questionnaire, created for this study, included information about socio-demographic characteristics, aeronautical experience, lifestyle, sleep habits, an Epworth sleepiness scale, and screening tests for chronic insomnia, sleep apnea syndrome and restless legs syndrome. Results749 aircrew members were included (86.2% male, 58.9% civilian, 74.1% pilot, mean age 43.4 ± 9.6 years), 45.9% of the population had at least one sleep disorder (chronic insomnia 39.5%, sleep apnea syndrome 10.5%, restless legs syndrome 4.1%), 15.5% had an excessive daytime sleepiness, and 24.6% reported in-flight sleep while on duty. Chronic insomnia, screen use before bedtime, use of sleeping pills, inadequate recovery time after a flight, female gender and civilian status were found as risk factors of in-flight sleep in the multivariate analysis. Conclusionthis study emphasizes the need to improve the screening and prevention of sleep disorders in this particular population.

Pilot In-Flight Sleep During Long-Range and Ultra-Long Range Commercial Airline Flights.

INTRODUCTION: In commercial aviation, pilot fatigue is a major threat to safety. One key fatigue mitigation strategy on long-range (LR; 8-16 h) and ultra-long range (ULR; 16+ h on at least 10% of trips) routes is allotting in-flight rest breaks for the pilots. Since sleep is a strong predictor of performance, it is important to quantify total in-flight sleep (TIFS) and determine rest scheme schedules that optimize sleep opportunity and subsequent performance. Here we quantify in-flight sleep and characterize rest schemes by type and efficiency.METHODS: Between 2015 and 2019, we collected data on in-flight sleep on 3 LR and 5 ULR routes totaling 231 pilots flying over 1200 flight duty periods. Data were collected using a combination of actigraphy and logbooks.RESULTS: Over all combinations of flight direction, crew and LR vs. ULR, average TIFS ranged from 3.4 h to 5.2 h with some ULR pilots getting over 8 h. Most crews made use of simple two- or three-break rest schemes and the complex four-break rest schemes were used almost exclusively on the three longest ULR routes. The complex schemes were less efficient than simple schemes, although this effect was small. Complex schemes resulted in no more TIFS compared to simple schemes on the same routes.DISCUSSION: Overall, we find that crews are getting more sleep on these routes than previously reported on similar routes. Most crews use simple rest schemes and these simple schemes are more efficient than complex schemes.Rempe MJ, Basiarz E, Rasmussen I, Belenky G, Lamp A. Pilot in-flight sleep during long-range and ultra-long range commercial airline flights. Aerosp Med Hum Perform. 2022; 93(4):368-375.

Predictive Biomathematical Modeling Compared to Objective Sleep During COVID-19 Humanitarian Flights.

BACKGROUND: Biomathematical modeling software like the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) model and Fatigue Avoidance Scheduling Tool (FAST) help carriers predict fatigue risk for planned rosters. The ability of a biomathematical model to accurately estimate fatigue risk during unprecedented operations, such as COVID-19 humanitarian ultra-long-range flights, is unknown. Azul Cargo Express organized and conducted five separate humanitarian missions to China between May and July 2020. Prior to conducting the missions, a sleep-prediction algorithm (AutoSleep) within SAFTE-FAST was used to predict in-flight sleep duration and pilot effectiveness. Here we compare AutoSleep predictions against pilots' sleep diary and a sleep-tracking actigraphy device (Zulu watch, Institutes for Behavior Resources) from Azul's COVID-19 humanitarian missions.METHODS: Pilots wore Zulu watches throughout the mission period and reported sleep duration for their in-flight rest periods using a sleep diary. Agreement between AutoSleep, diary, and Zulu watch measures was compared using intraclass correlation coefficients (ICC). Goodness-of-fit between predicted effectiveness distribution between scenarios was evaluated using the R² statistic.RESULTS: A total of 20 (N = 20) pilots flying across 5 humanitarian missions provided sleep diary and actigraphy data. ICC and R² values were >0.90, indicating excellent agreement between sleep measures and predicted effectiveness distribution, respectively.DISCUSSION: Biomathematical predictions of in-flight sleep during unprecedented humanitarian missions were in agreement with actual sleep patterns during flights. These findings indicate that biomathematical models may retain accuracy even under extreme circumstances. Pilots may overestimate the amount of sleep that they receive during extreme flight-duty periods, which could constitute a fatigue risk.Devine JK, Garcia CR, Simoes AS, Guelere MR, de Godoy B, Silva DS, Pacheco PC, Choynowski J, Hursh SR. Predictive biomathematical modeling compared to objective sleep during COVID-19 humanitarian flights. Aerosp Med Hum Perform. 2022; 93(1):4-12.

Business Class Travel Preserves Sleep Quality and Quantity and Minimizes Jet Lag During the ICC Women's T20 World Cup.

To determine the impact of the quality and quantity of sleep during an international flight on subsequent objective sleep characteristics, training and match-day load, self-reported well-being, and perceptions of jet lag of elite female cricketers during an International Cricket Council Women's T20 World Cup. In-flight and tournament objective sleep characteristics of 11 elite female cricketers were assessed using activity monitors. Seated in business class, players traveled west from Melbourne, Australia, to Chennai, India. The outbound flight departed Melbourne at 3:30 AM with a stopover in Dubai for 2 hours. The arrival time in Chennai was 8:10 PM local time (1:40 AM in Melbourne). The total travel time was 19 hours 35 minutes. Perceptual ratings of jet lag, well-being, and training and competition load were collected. To determine the impact of in-flight sleep on tournament measures, a median split was used to create subsamples based on (1)in-flight sleep quantity and (2)in-flight sleep quality (2 groups: higher vs lower). Spearman correlation coefficients were calculated to assess the bivariate associations between sleep measures, self-reported well-being, perceptual measures of jet lag, and internal training and match-day load. Mean duration and efficiency of in-flight sleep bouts were 4.72 hours and 87.45%, respectively. Aggregated in-flight sleep duration was 14.64 + 3.56 hours. Players with higher in-flight sleep efficiency reported higher ratings for fatigue (ie,lower perceived fatigue) during the tournament period. Tournament sleep duration was longer, and bed and wake times were earlier compared with habitual. Compared with other nights during the tournament, sleep duration was shorter following matches. Maximizing in-flight sleep quality and quantity appears to have implications for recovery and sleep exhibited during competition. Sleep duration was longer than habitual except for the night of a match, which suggests that T20 matches may disrupt sleep duration.

Pilot Sleep Behavior across Time during Ultra-Long-Range Flights.

Fatigue risk to the pilot has been a deterrent for conducting direct flights longer than 12 h under normal conditions, but such flights were a necessity during the COVID-19 pandemic. Twenty (N = 20) pilots flying across five humanitarian missions between Brazil and China wore a sleep-tracking device (the Zulu watch), which has been validated for the estimation of sleep timing (sleep onset and offset), duration, efficiency, and sleep score (wake, interrupted, light, or deep Sleep) throughout the mission period. Pilots also reported sleep timing, duration, and subjective quality of their in-flight rest periods using a sleep diary. To our knowledge, this is the first report of commercial pilot sleep behavior during ultra-long-range operations under COVID-19 pandemic conditions. Moreover, these analyses provide an estimate of sleep score during in-flight sleep, which has not been reported previously in the literature.

292 Rest Schemes and Inflight Sleep Duration on Long Range and Ultra-Long Range Commercial Airline Routes

Abstract Introduction Pilots flying long range (LR; 8-16 hour) and ultra-long range (ULR; 16+ hour on 10% of trips) commercial airline routes use a variety of work/rest schedules during flights, resulting in a wide distribution of total inflight sleep time (TIFS) amounts. Since sleep is a strong predictor of performance, it is important to quantify TIFS and determine rest scheme patterns that optimize sleep opportunity and subsequent alertness and performance. Here we report rest schemes for pilots on LR and ULR routes and longer TIFS values than previously reported. These rest schemes can serve as templates to increase TIFS and improve pilot performance, particularly on ULR routes. Methods 427 commercial airline pilots provided data for this sub-study that was part of a larger study on Fatigue Risk Management System (FRMS) routes. Inflight sleep timing and duration were measured on 3 LR and 5 ULR routes. Inflight sleep times were self-reported in a sleep/work logbook and verified using actigraphy. Results Most outbound and inbound landing crews took one break during the second half of the flight (average LR TIFS=4.0 hr; average ULR TIFS=4.9 hr), while most outbound and inbound relief crews consequently took one break during the first half of the flight (average LR TIFS=3.5 hr; average ULR TIFS=4.5 hr). However, three of the five ULR routes used more complex split rest schemes for landing and relief crews, primarily on outbound flights (average TIFS=5.0 hr). Across all routes and both crews, the maximum average TIFS reached ~6 hours. Conclusion Our results indicate that pilots on average are sleeping inflight more than previous studies demonstrated. Additionally, we found that crews on some ULR flights used more complicated rest schemes, but still generally preferred 2 or 3 breaks. These findings have implications for airline procedures and aviation policies by showing that pilots may be sleeping longer than originally expected on LR and ULR flights. Recommending rest schemes that allow for the greatest inflight sleep opportunity may provide the best chance for inflight recuperation, especially before the Top of Descent critical phase of flight. Support (if any) United Airlines

313 Sleep Obtained by Cabin Crewmembers During a Long-haul Flight

Abstract Introduction Sleep loss and circadian disruption pose a significant risk in safety-sensitive occupations. In aviation, many studies have demonstrated how inflight rest locations influence alertness and performance among pilots, but few studies have evaluated cabin crew. The purpose of the present study was to evaluate sleep outcomes among cabin crewmembers sleeping in a bunk compared to a jump seat during one long-haul route. Methods Thirty-one (6 male) cabin crewmembers (age M = 30, SD = +/-13) flew the same long-haul route (outbound and return) with a flight duration of 10:41 (± 0:14) hours. Participants were randomly assigned to fly on an aircraft with a bunk or a jump seat for their sleep opportunity. Participants wore an Actiwatch (Phillips-Respironics Spectrum) throughout the entire study and completed a sleep diary at bedtime and upon waking. During flight they completed a nap diary entering the start time of the inflight sleep (if any) and the duration. Results Sixty-five flights (32 outbound and 33 return) were included in the analyses. Seventy-seven percent of the flights had a bunk and 23% had a jump seat. Crewmembers obtained M = 146.46 (± 67.20) minutes of rest out of which they slept M = 125.33 (± 64.91) minutes in the bunk. While using the jump seat, crewmembers obtained M = 169.53 (± 133.30) minutes of rest out of which they slept M = 142.92 (± 149.72) minutes. When crewmembers slept in the bunk, sleep latency was shorter (M = 13.69 ± 12.64 minutes) and efficiency was better (M = 76.16 ± 16.09 %) compared to the jump seat (sleep onset: M = 16.77 ± 13.89 minutes; sleep efficiency: M = 60.64 ± 17.42 %). Conclusion We found that cabin crewmembers slept for longer time when they used the jump seat. They fell asleep faster and their sleep efficiency was better when using the bunk compared to the jump seat. Further research is needed to understand how sleep quality and subsequent performance are influenced by sleep opportunity in a bunk compared to a jump seat. Support (if any) NASA Airspace Operations and Safety Program, System-Wide Safety Project.

286 Pilot Sleep During Brazil-to-China COVID-19 Humanitarian Mission Flights Compared to Biomathematical Predictions of Sleep

Introductionn response to the COVID-19 pandemic, Azul Airlines organized and conducted five separate humanitarian missions to China between May and July, 2020. Each mission consisted of 4 flight legs between 11-15 hours long crewed by a team of 8 pilots. Each pilot was given a 9-hour sleep opportunity during the flight period. Prior to conducting the missions, a sleep-prediction algorithm (AutoSleep) within the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) model Fatigue Avoidance Scheduling Tool (FAST) was used to predict in-flight time in bed (TIB) and total sleep time (TST). During missions, pilots wore a wrist actigraph and completed a sleep diary. These analyses compare the accuracy of SAFTE-FAST AutoSleep predictions against pilots’ sleep diary and actigraphy from Azul’s COVID-19 humanitarian missions.MethodsPilots wore a sleep-tracking actigraphy device (Zulu Watch, Institutes for Behavior Resources), and reported the TIB and sleep quality of their in-flight rest periods using a sleep diary. Diary TST was estimated from TIB and sleep quality. AutoSleep, diary, and actigraphy measures were compared using paired samples t-tests. Agreement was compared using intraclass correlation coefficients (ICC).ResultsTwenty (n=20) pilots flying across 5 humanitarian missions provided sleep diary and actigraphy data. AutoSleep predictions of TIB (235±20 minutes) and TST (193±16 minutes) were significantly lower than diary (TIB: 330±123, t=6.80, p≤0.001; TST: 262±108, t=5.60, p≤0.001) and comparable to actigraphy (TIB: 246±127, t=0.78, p=0.43; TST: 212±113, t=1.59, p=0.12). ICC values were >0.90, indicating excellent agreement, for TIB (0.94) and TST (0.91).ConclusionBiomathematical predictions of in-flight sleep during unprecedented humanitarian missions were in agreement with actual sleep patterns during flights. These findings indicate that biomathematical models may retain accuracy even under extreme circumstances like the COVID-19 pandemic. Pilots may overestimate the amount of sleep that they receive during extreme flights-duty periods, which could constitute a fatigue risk.Support (if any)NA

Flight Crew Alertness and Sleep Relative to Timing of In-Flight Rest Periods in Long-Haul Flights.

BACKGROUND: In-flight breaks are used during augmented long-haul flight operations, allowing pilots a sleep opportunity. The U.S. Federal Aviation Administration duty and rest regulations restrict the pilot flying the landing to using the third rest break. It is unclear how effective these restrictions are on pilots ability to obtain sleep. We hypothesized there would be no difference in self-reported sleep, alertness, and fatigue between pilots taking the second vs. third rest breaks.METHODS: Pilots flying augmented operations in two U.S.-based commercial airlines were eligible for the study. Volunteers completed a survey at top-of-descent (TOD), including self-reported in-flight sleep duration, and Samn-Perelli fatigue and Karolinska Sleepiness Scale ratings. We compared the second to third rest break using noninferiority analysis. The influence of time of day (home-base time; HBT) was evaluated in 4-h blocks using repeated measures ANOVA.RESULTS: From 787 flights 500 pilots provided complete data. The second rest break was noninferior to the third break for self-reported sleep duration (1.5 0.7 h vs. 1.4 0.7 h), fatigue (2.0 1.0 vs. 2.9 1.3), and sleepiness (2.6 1.4 vs. 3.8 1.8) at TOD for landing pilots. Measures of sleep duration, fatigue, and sleepiness were influenced by HBT circadian time of day.DISCUSSION: We conclude that self-reported in-flight sleep, fatigue, and sleepiness from landing pilots taking the second in-flight rest break are equivalent to or better than pilots taking the third break. Our findings support providing pilots with choice in taking the second or third in-flight rest break during augmented operations.Gregory KB, Soriano-Smith RN, Lamp ACM, Hilditch CJ, Rempe MJ, Flynn-Evans EE, Belenky GL. Flight crew alertness and sleep relative to timing of in-flight rest periods in long-haul flights. Aerosp Med Hum Perform. 2021; 92(2):8391.

0210 Evaluating the Sensitivity of Sleep Measures for Monitoring Pilot Fatigue in Operational Settings

Abstract Introduction Previously, combined data analyses of four pilot fatigue monitoring studies including 237 pilots flying long-haul and ultra-long range (ULR) flights found no association between pilots’ actigraphic sleep in flight and psychomotor vigilance task (PVT) performance at top-of-descent (TOD; beginning of the landing phase of flight). The present study aimed to determine whether measures of in-flight sleep recorded with polysomnography (PSG) are more sensitive predictors of pilots’ PVT performance near TOD than actigraphic measures. Methods Data were re-analysed from 41 Singapore Airlines A340-500 pilots (median age 47, range 29–58 years) monitored on a ULR trip between Singapore and Los Angeles (average flight duration outbound = 15.6 hrs; inbound = 17.2 hrs). In-flight sleep was recorded simultaneously with PSG (scored in 30-second epochs) and actigraphy (recorded in 30-second epochs and scored in conjunction with sleep diary information). PSG- and actigraphy-determined time awake were calculated as the duration between the end of the last epoch scored as sleep (PSG) or software-scored sleep interval (actigraphy) and the start time of the 10-minute PVT completed near TOD. Results Linear mixed modelling indicated that after controlling for flight sector and intra- and inter-individual variability, neither PSG-derived total in-flight sleep (F (1, 44.4) = 0.006, p= 0.941) and time awake (F (1, 34.3) = 0.431, p= 0.516), nor actigraphic total in-flight sleep (F (1, 51.1) = 0.161, p= 0.69) and time awake (F (1, 34.9) = 0.23, p= 0.634) were associated with PVT response speed at TOD. Conclusion In this context, actigraphy produced identical findings to polysomnography and remains a valid alternative for monitoring in-flight sleep of groups of pilots during ULR flights. Further research is needed to determine whether PVT performance is a discriminatory measure of fatigue-related impairment in pilots. Support This analysis was supported by the Massey University College of Health Research Fund. The Singapore Airlines study was funded by the Singapore Civil Aviation Authority. We thank Dr Jarnail Singh for permission to use these data.

Aviation Human Factors Related Industry News

Aviation Human Factors Related Industry News

Shared responsibility for managing fatigue: Hearing the pilots.

In commercial aviation, fatigue is defined as a physiological state of reduced mental or physical performance capability resulting from sleep loss, extended wakefulness, circadian phase, and/or workload. The International Civil Aviation Organisation mandates that responsibility for fatigue risk management is shared between airline management, pilots, and support staff. However, to date, the majority of research relating to fatigue mitigations in long range operations has focused on the mitigations required or recommended by regulators and operators. Little research attention has been paid to the views or operational experience of the pilots who use these (or other) mitigations. This study focused on pilots’ views and experiences of in-flight sleep as the primary fatigue mitigation on long range flights. It also sought information about other fatigue mitigation strategies they use. Thematic analysis was used to explore written comments from diary and survey data collected during long range and ultra-long range trips (N = 291 pilots on three different aircraft types, 17 different out-and-back trips, and four airlines based on three continents). The findings indicate that the recommended fatigue mitigation strategies on long-haul flights (particularly in-flight sleep) are effective and well-utilised, consistent with quantitative findings from the same trips. Importantly however, the analyses also highlight areas that require further investigation, including flight preparation strategies in relation to the uncertainty of in-flight break allocation. There were two strategies for sleep prior to a flight: maximising sleep if pilots were expecting later breaks in the flight; or minimising sleep if they were expecting breaks earlier or at unfavourable times in the circadian cycle. They also provide a broader view of the factors that affect the amount and quality of pilots’ in-flight sleep, about which evidence has previously been largely anecdotal. The study underscores the value of including the views and experience of pilots in fatigue risk management.

Equivalence Testing as a Tool for Fatigue Risk Management in Aviation.

Many civilian aviation regulators favor evidence-based strategies that go beyond hours-of-service approaches for managing fatigue risk. Several countries now allow operations to be flown outside of flight and duty hour limitations, provided airlines demonstrate an alternative method of compliance that yields safety levels "at least equivalent to" the prescriptive regulations. Here we discuss equivalence testing in occupational fatigue risk management. We present suggested ratios/margins of practical equivalence when comparing operations inside and outside of prescriptive regulations for two common aviation safety performance indicators: total in-flight sleep duration and psychomotor vigilance task reaction speed. Suggested levels of practical equivalence, based on expertise coupled with evidence from field and laboratory studies, are ≤ 30 min in-flight sleep and ± 15% of reference response speed. Equivalence testing is illustrated in analyses of a within-subjects field study during an out-and-back long-range trip. During both sectors of their trip, 41 pilots were monitored via actigraphy, sleep diary, and top of descent psychomotor vigilance task. Pilots were assigned to take rest breaks in a standard lie-flat bunk on one sector and in a bunk tapered 9 from hip to foot on the other sector. Total in-flight sleep duration (134 ± 53 vs. 135 ± 55 min) and mean reaction speed at top of descent (3.94 ± 0.58 vs. 3.77 ± 0.58) were equivalent after rest in the full vs. tapered bunk. Equivalence testing is a complimentary statistical approach to difference testing when comparing levels of fatigue and performance in occupational settings and can be applied in transportation policy decision making.Wu LJ, Gander PH, van den Berg M, Signal TL. Equivalence testing as a tool for fatigue risk management in aviation. Aerosp Med Hum Perform. 2018; 89(4):383-388.

Development of a smart garment for the assessment of cardiac mechanical performance and other vital signs during sleep in microgravity

Several aspects of sleep physiology in microgravity are still unclear. In the frame of the Wearable Monitoring project, part of the Futura Mission of the Italian Space Agency, we developed a new smart garment (MagIC-Space) for the monitoring of the cardiac mechanical activity and other vital signs during sleep in space missions. The system is composed of 4 components: 1) a sensorized vest, including textile sensors for the detection of ECG and respiratory frequency, 2) an electronic module, collecting data from the vest and including two accelerometers for the seismocardiogram measure, from which indexes of cardiac mechanics are derived on a beat-to-beat basis, 3) an external probe for the assessment of the thorax skin temperature, and 4) a battery unit for the system power supply. From January till June 2015 seven inflight sleep recordings were made aboard the International Space Station by using two MagIC-Space systems. Data were collected to investigate the cardiovascular effects of microgravity during sleep. The positive performance aboard and the good quality of the recorded signals (>96% of the collected data could be used for the subsequent analyses), validate the proposed system architecture and support its possible exploitation in future flights and on Earth.

Equal to or better than: The application of statistical non-inferiority to fatigue risk management

In December 2014, the Federal Aviation Administration (FAA) completed a major revision of the rules and regulations governing flight and duty time in commercial aviation (Federal Aviation Regulation (FAR) Part 117). Scientists were included in the revision process and provided insights into sleep, sleep loss, the circadian rhythm, and their effects on performance that were incorporated into the new rule. If a planned flight was non-compliant with the regulation, for example if it exceeded flight and duty time limits, it could only be flown under an FAA-approved Fatigue Risk Management System (FRMS) as meeting an Alternative Method of Compliance (AMOC). One method that a flight could qualify as an AMOC is if it could be demonstrated empirically that it was as safe as or safer than a similar flight, designated the Safety Standard Operation (SSO), that was compliant with the regulation. In the present paper, we demonstrate the FRMS process using a comparison between a non-compliant AMOC flight from the US west coast to Australia and a compliant SSO flight from the US west coast to Taiwan. The AMOC was non-compliant because it exceeded the flight time limits in the prescriptive rule. Once a data collection exemption was granted by the FAA, both the outbound and inbound AMOC and SSO routes were studied on four Safety Performance Indicators (SPIs). The SPIs studied were inflight sleep, cognitive performance, self-reported fatigue, and self-reported sleepiness. These measures were made at top of descent (TOD), a critical phase of flight. The study was designed as a paired comparison. Forty volunteer pilots studied flew both the AMOC and the SSO flights for a total of 80 studied flights. Using statistical non-inferiority applied to the AMOC and SSO SPIs, we demonstrated, as required by the new rule, that the US-Australia AMOC flight was “as safe as, or safer than” the US-Taiwan SSO flight. In the context of FRMS, statistical non-inferiority is a concept and technique of great utility, straightforward in application, producing clear visual representations of the findings, and providing a direct answer to the question posed by the regulation - is the AMOC flight "as safe as, or safer than” the SSO.

Subjective Measurements of In-Flight Sleep, Circadian Variation, and Their Relationship with Fatigue.

This study examined whether subjective measurements of in-flight sleep could be a reliable alternative to actigraphic measurements for monitoring pilot fatigue in a large-scale survey. Pilots (3-pilot crews) completed a 1-page survey on outbound and inbound long-haul flights crossing 1-7 time zones (N = 586 surveys) between 53 city pairs with 1-d layovers. Across each flight, pilots documented flight start and end times, break times, and in-flight sleep duration and quality if they attempted sleep. They also rated their fatigue (Samn-Perelli Crew Status Check) and sleepiness (Karolinska Sleepiness Scale) at top of descent (TOD). Mixed model ANCOVA was used to identify independent factors associated with sleep duration, quality, and TOD measures. Domicile time was used as a surrogate measure of circadian phase. Sleep duration increased by 10.2 min for every 1-h increase in flight duration. Sleep duration and quality varied by break start time, with significantly more sleep obtained during breaks starting between (domicile) 22:00-01:59 and 02:00-05:59 compared to earlier breaks. Pilots were more fatigued and sleepy at TOD on flights arriving between 02:00-05:59 and 06:00-09:59 domicile time compared to other flights. With every 1-h increase in sleep duration, sleepiness ratings at TOD decreased by 0.6 points and fatigue ratings decreased by 0.4 points. The present findings are consistent with previous actigraphic studies, suggesting that self-reported sleep duration is a reliable alternative to actigraphic sleep in this type of study, with use of validated measures, sufficiently large sample sizes, and where fatigue risk is expected to be low. van den Berg MJ, Wu LJ, Gander PH. Subjective measurements of in-flight sleep, circadian variation, and their relationship with fatigue. Aerosp Med Hum Perform. 2016; 87(10):869-875.

Mitigating and monitoring flight crew fatigue on a westward ultra-long-range flight.

This study examined the uptake and effectiveness of fatigue mitigation guidance material including sleep recommendations for a trip with a westward ultra-long-range flight and return long-range flight. There were 52 flight crew (4-pilot crews, mean age 55 yr) who completed a sleep/duty diary and wore an actigraph prior to, during, and after the trip. Primary crew flew the takeoff and landing, while relief crew flew the aircraft during the Primary crew's breaks. At key times in flight, crewmembers rated their fatigue (Samn-Perelli fatigue scale) and sleepiness (Karolinska Sleepiness Scale) and completed a 5-min Psychomotor Vigilance Task. Napping was common prior to the outbound flight (54%) and did not affect the quantity or quality of in-flight sleep (mean 4.3 h). Primary crew obtained a similar amount on the inbound flight (mean 4.0 h), but Secondary crew had less sleep (mean 2.9 h). Subjective fatigue and sleepiness increased and performance slowed across flights. Performance was faster on the outbound than inbound flight. On both flights, Primary crew were less fatigued and sleepy than Secondary crew, particularly at top of descent and after landing. Crewmembers slept more frequently and had more sleep in the first 24 h of the layover than the last, and had shifted their main sleep to the local night by the second night. The suggested sleep mitigations were employed by the majority of crewmembers. Fatigue levels were no worse on the outbound ultra-long-range flight than on the return long-range flight.