Sleep Environment Recommendations for Future Spaceflight Vehicles

Current evidence demonstrates that astronauts experience sleep loss and circadian desynchronization during spaceflight. Ground-based evidence demonstrates that these conditions lead to reduced performance, increased risk of injuries and accidents, and short and long-term health consequences. Many of the factors contributing to these conditions relate to the habitability of the sleep environment. Noise, inadequate temperature and airflow, and inappropriate lighting and light pollution have each been associated with sleep loss and circadian misalignment during spaceflight operations and on Earth. As NASA prepares to send astronauts on long-duration, deep space missions, it is critical that the habitability of the sleep environment provide adequate mitigations for potential sleep disruptors. We conducted a comprehensive literature review summarizing optimal sleep hygiene parameters for lighting, temperature, airflow, humidity, comfort, intermittent and erratic sounds, and privacy and security in the sleep environment. We reviewed the design and use of sleep environments in a wide range of cohorts including among aquanauts, expeditioners, pilots, military personnel and ship operators. We also reviewed the specifications and sleep quality data arising from every NASA spaceflight mission, beginning with Gemini. Finally, we conducted structured interviews with individuals experienced sleeping in non-traditional spaces including oil rig workers, Navy personnel, astronauts, and expeditioners. We also interviewed the engineers responsible for the design of the sleeping quarters presently deployed on the International Space Station. We found that the optimal sleep environment is cool, dark, quiet, and is perceived as safe and private. There are wide individual differences in the preferred sleep environment; therefore modifiable sleeping compartments are necessary to ensure all crewmembers are able to select personalized configurations for optimal sleep. A sub-optimal sleep environment is tolerable for only a limited time, therefore individual sleeping quarters should be designed for long-duration missions. In a confined space, the sleep environment serves a dual purpose as a place to sleep, but also as a place for storing personal items and as a place for privacy during non-sleep times. This need for privacy during sleep and wake appears to be critically important to the psychological well-being of crewmembers on long-duration missions

Fatigue, Schedules, Sleep, and Sleepiness in U.S. Commercial Pilots During COVID-19

cOViD-19 has had a significant impact on the aviation industry. While reduced flying capacity may intuitively translate to reduced fatigue risk by way of fewer flights and duty hours, the actual impact of the pandemic on pilot fatigue is unknown. methods: We surveyed U.S. commercial airline pilots in late 2020 (N = 669) and early 2021 (N = 156) to assess the impact of COViD-19 on schedules and fatigue during the pandemic. results: Overall, pilots reported reduced flight and duty hours compared to prepandemic. Average sleep on workdays was slightly shorter in late 2020 (6.87 ± 1.14 h) and recovered to prepandemic levels in early 2021 (6.95 ± 1.11 h). Similarly, the frequency of sleepiness on days off and in-flight increased in late 2020, with 54% of pilots reporting an increase in in-flight sleepiness, then returned to prepandemic levels in early 2021. the use of in-flight sleepiness countermeasures remained the same across assessed time points. Pilots highlighted several factors which impacted their sleep and job performance, including limited access to nutritional food during duty days and layovers, reduced access to exercise facilities during layovers, increased stress due to job insecurity and health concerns, increased distractions and workload, and changes to scheduling. discussion: Despite a reduction in flights and duty days, COViD-19 led to increased sleepiness on days off and in flight, potentially due to the negative impact of lack of access to essential needs and heightened stress on sleep. Operators need to monitor the change in these COViD-19 related risks as the industry returns to full service

Controlled Rest: Profile of Use, Challenges, and Best Practices

Despite the introduction of flight, duty, and rest time regulations to reduce the risk of sleepiness, airline pilots often encounter elevated sleepiness during flight. To combat this sleepiness, in some instances, pilots can take a short nap on the flight deck (controlled rest) to improve their alertness. Little is known, however, as to when and how often this countermeasure is used operationally. Methods: Forty-four pilots from a European carrier wore actiwatches and filled in an electronic sleep and work diary for approximately 2 weeks resulting in data from 239 flights. Self-reported in-flight rest periods were used to set rest intervals and sleep was estimated within these intervals using Philips Actiware 6.0.9. Wake threshold selection was set to medium; sleep threshold detection algorithm was set to 10 immobile minutes at sleep onset and sleep end. Timing of sleep periods was analyzed relative to home base time. Results: Preliminary analyses showed that controlled rest was taken on 46% (n=110) of flights. On 23 flights (10%) pilots reported taking two controlled rest periods. Sleep, as estimated by actigraphy, was achieved during 80% (n=106) of controlled rest periods. The mean sleep duration was 32 ( 12) minutes estimated within successful controlled rest periods. Approximately two-thirds (67.5%, n=81) of all rest periods were initiated during home base time night (0000h-0800h). On 11% (n=26) of flights, pilots also reported taking bunk rest (longer rest period in a designated sleeping facility).Conclusion:This study shows that controlled rest is commonly used as a countermeasure to sleepiness on the flight deck. Further analysis is required to determine what other factors contribute to the decision to take controlled rest, and how effective it is in reducing sleepiness on the flight deck

A Summary Of: Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Sleep loss and circadian misalignment contribute to a meaningful proportion of operational accidents and incidents. Countermeasures and work scheduling designs aimed at mitigating fatigue are typically evaluated in controlled laboratory environments, but the effectiveness of translating such strategies to operational environments can be challenging to assess. This manuscript summarizes an approach for collecting sleep, circadian, fatigue, and performance data in a complex operational environment. We studied 44 airline pilots over 34 days while they flew a fixed schedule, which included a baseline data collection with 5 days of mid-morning flights, four early flights, four high-workload mid-day flights, and four late flights that landed after midnight. Each work block was separated by 3-4 days of rest. To assess sleep, participants wore a wrist-worn research-validated activity monitor continuously and completed daily sleep diaries. To assess the circadian phase, pilots were asked to collect all urine produced in four or eight hourly bins during the 24 h after each duty block for the assessment of 6-sulfatoxymelatonin (aMT6s), which is a biomarker of the circadian rhythm. To assess subjective fatigue and objective performance, participants were provided with a touchscreen device used to complete the Samn-Perelli Fatigue Scale and Psychomotor Vigilance Task (PVT) during and after each flight, and at wake-time, mid-day, and bedtime. Using these methods, it was found that sleep duration was reduced during early starts and late finishes relative to baseline. Circadian phase shifted according to duty schedule, but there was a wide range in the aMT6s peak between individuals on each schedule. PVT performance was worse on the early, high-workload, and late schedules relative to baseline. Overall, the combination of these methods was practical and effective for assessing the influence of sleep loss and circadian phase on fatigue and performance in a complex operational environment

Sleep Environment Recommendations for Future Spaceflight Vehicles

Evidence from spaceflight and ground-based missions demonstrate that sleep loss and circadian desynchronization occur among astronauts, leading to reduced performance and, increased risk of injuries and accidents. We conducted a comprehensive literature review to determine the optimal sleep environment for lighting, temperature, airflow, humidity, comfort, intermittent and erratic sounds, privacy and security in the sleep environment. We reviewed the design and use of sleep environments in a wide range of cohorts including among aquanauts, expeditioners, pilots, military personnel, and ship operators. We also reviewed the specifications and sleep quality data arising from every NASA spaceflight mission, beginning with Gemini. We found that the optimal sleep environment is cool, dark, quiet, and is perceived as safe and private. There are wide individual differences in the preferred sleep environment; therefore modifiable sleeping compartments are necessary to ensure all crewmembers are able to select personalized configurations for optimal sleep

Best Practices for Fatigue Risk Management in Non-Traditional Shiftwork

Fatigue risk management programs provide effective tools to mitigate fatigue among shift workers. Although such programs are effective for typical shiftwork scenarios, where individuals of equal skill level can be divided into shifts to cover 24 hour operations, traditional programs are not sufficient for managing sleep loss among individuals with unique skill sets, in occupations where non-traditional schedules are required. Such operations are prevalent at NASA and in other high stress occupations, including among airline pilots, military personnel, and expeditioners. These types of operations require fatigue risk management programs tailored to the specific requirements of the mission. Without appropriately tailored fatigue risk management, such operations can lead to an elevated risk of operational failure, disintegration of teamwork, and increased risk of accidents and incidents. In order to design schedules for such operations, schedule planners must evaluate the impact of a given operation on circadian misalignment, acute sleep loss, chronic sleep loss and sleep inertia. In addition, individual-level factors such as morningness-eveningness preference and sleep disorders should be considered. After the impact of each of these factors has been identified, scheduling teams can design schedules that meet operational requirements, while also minimizing fatigue

Circadian and Fatigue Effects on the Dynamics of the Pupillary Light Reflex

The pupillary light reflex (PLR) is known to be driven by the photo-entrainment of intrinsically-photosensitive retinal ganglion cells. These ganglion cells are known to have retino-hypothalamic projections to the suprachiasmatic nuclei (SCN), which regulates circadian rhythms, and bilateral retinal projections to the pretectal area, which mediates the PLR (Dacey et al., 2005; Hattar et al., 2002, 2006). The magnitude of the PLR has previously been shown to show circadian variation (Mnch et al., 2012). In this study, we used a constant routine protocol (Mills et al., 1978) to examine circadian and fatigue effects on the dynamics of the PLR. We characterized the PLR (pupil size as a function of time) in response to a square-wave change in the luminance of a white display background, at ten different times over a single circadian cycle. Twelve subjects participated in three daytime baseline runs followed by 7 nighttime runs each separated by an hour (17 23 hours after awakening). The constriction and dilation phases of the PLR waveform were fit separately with a single exponential model (Longtin Milton, 1988; Milton Longtin, 1990) with time constants estimated using a least-squares method. The dilation time constant exhibited a distinct sinusoidal modulation across the circadian cycle and, after 23 hours of wakefulness, decreased on average by 82 ms (paired t-test, p 0.05) relative to baseline (mean: 543 ms). The constriction time constant however, did not show an overall decrease with increased wakefulness. We conclude that the dynamics of the PLR show circadian variation and that, in addition, the briskness of the dilation response to a step-decrease in luminance shows a homeostatic enhancement with increased wakefulness

Machine Learning Prototype App For Recognition of Fruits

As the incidence of obesity and associated negative health consequences is rising, it becomes crucial to monitor the dietary choices of individuals. Unfortunately, traditional methods to collect this information involve collecting food frequency questionnaires from individuals using paper. Electronic food trackers have been developed to collect food data, but they require participants to manually label and describe the content of their meals, and which may be difficult for researchers to interpret in a standardized fashion. Machine learning, however, provides an easy and efficient method for both participants and researchers to label food items with standardized descriptions. This project aims to create a prototype phone application that can identify and label photos of apples. This is done by making a machine learning model through Turicreate, a python module, which is then implemented into an iOS app through Xcode and Swift. The modules used in Swift include CoreML and AVFoundation. This machine learning application will be incorporated with a MealLogger phone app that is also under development. The MealLogger app will be used to keep track of participants' calorie intake and other personal details throughout the sleep study. The machine learning model will present several potential identities of the foods found in the photo, and the user will only need to select the correct option. This will be a user-friendly method for participants to easily log their food consumption without the hard work of manually inputting each and every description. Some limitations to this project include the wide variety of food, including those within different cultures. To deal with this, the model will include the most generic food categories, which the participant may select, and produce a drop-down menu of more specific dishes under that specified category, with the option of self-input. Additional questionnaires may be implemented according to the food type selected This will allow the process to be quick and easy, but also specific for the purpose of analysis. The release of the application will require a much longer process, but the machine learning prototype presents a first step toward an application that may change data analysis for researchers interested in collecting food intake from individuals living in the real world

Microlensing of Globular Clusters as a Probe of Galactic Structure

The spatial distribution of compact dark matter in our Galaxy can be determined in a few years of monitoring Galactic globular clusters for microlensing. Globular clusters are the only dense fields of stars distributed throughout the three-dimensional halo and hence are uniquely suited to probe its structure. The microlensing optical depths towards different clusters have varying contributions from the thin disk, thick disk, bulge, and halo of the Galaxy. Although measuring individual optical depths to all the clusters is a daunting task, we show that interesting Galactic structure information can be extracted with as few as $40$--$120$ events in total for the entire globular cluster system (observable with 2--5 years of monitoring). The globular cluster microlensing is particularly sensitive to the core radius of the halo mass distribution and to the scale length, surface mass density, and radial scale height variations of the thin disk.Comment: 14 pages, 1 figure. Submitted to ApJ Letters. Uses aastex macro

Mitigating fatigue on the flight deck: how is controlled rest used in practice?

Controlled Rest (CR) refers to a short, unscheduled, voluntary nap opportunity taken by pilots on the flight deck as a countermeasure to unanticipated fatigue in flight. This study explores the profile of CR use in a long-haul commercial airline. Forty-four pilots wore actiwatches and filled in an application-based sleep/work diary for approximately 2 weeks resulting in complete records from 239 flights. Timing of sleep periods and flight schedules were analyzed relative to home-base time. Pearson correlations were used to assess the influence of pilot demographics on CR use. A mixed-effects logistic regression was used to analyze the impact of schedule factors on CR. CR was taken on 46% (n = 110) of flights, with 80% (n = 106/133) of all CR attempts (accounting for multiple CR attempts on 23 flights) estimated by actigraphy to have successfully achieved sleep. Average sleep duration during successful rest periods was estimated as 31.7 ± 12.2 min. CR was more frequent on 2-pilot (69%, n = 83) vs. \u3e2-pilot flights (23%, n = 27); return (60%, n = 71) vs. outbound flights (33%, n = 39); night (55%, n = 76) vs. day flights (34%, n = 34); and \u3c10 h (63%, n = 80) vs. \u3e10 h duration flights (27%, n = 30) (all p ≤ 0.001). There was no significant difference for direction of travel (eastbound: 51%, n = 57; westbound: 40%, n = 44; p = .059). Of note, 22% (n = 26) of augmented flights contained both CR and bunk rest. Data from this airline show that CR is most commonly used on flights with 2-pilot crews (\u3c10 h duration) and nighttime flights returning to base. Future studies are required to determine the generalizability of these results to other airlines