Engineering topics

Flynn-Evans, Erin E.

Publications and source records attributed to Flynn-Evans, Erin E..

17 records

NASA NTRS2020

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.

Arsintescu, Lucica↗

NASA NTRS2019

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.

Hilditch, Cassie J.↗

NASA NTRS2019

The Relationship between Workload, Performance and Fatigue in a Short-Haul Airline

Short-haul flights are associated with irregular work schedules and increased workload, due to frequent takeoffs and landings. We examined the relationship between pilot workload, performance and subjective fatigue during normal short-haul operations. Ninety airline pilots (8 female), mean age 33 (Â±8 years) completed a NASA-Task Load Index (NASA-TLX), a Psychomotor Vigilance Task (PVT; a reaction time test sensitive to sleep loss) and a Samn-Perelli (SP) fatigue scale, over a period of 20 duty days at top-of-descent on 2762 short-haul flights. The duty days included either 2 or 4 flights per day starting at different times as scheduled during normal operations. Workload was measured using the six NASA-TLX scales: mental demand, physical demand, temporal demand, effort, performance and frustration. Lapses (reaction times [RT] > 500ms) were calculated for the PVT. Spearman correlations were calculated to identify relationships between the NASA-TLX, PVT lapses, and SP. The six scales of NASA-TLX were positively correlated with the PVT lapses (p < 0.01) showing an increase in workload when lapses increased. There was a positive correlation between subjective fatigue as measured by the SP fatigue scale and each of the six scales of NASA-TLX (p < 0.001) suggesting that pilots reported higher workload when perceived levels of fatigue were higher. Of the six workload scales, mental demand and performance were rated the highest (mental: M = 40.99, SD = 20.32; performance: M = 41.61, SD = 20.71) and effort was rated the lowest (M = 15.59, SD = 8.98). Preliminary analyses suggest that high workload is associated with poorer PVT performance and increased self-reported fatigue in this population of short-haul pilots. Future studies should explore how other workload factors (i.e. flight hours, time of day) influence self-reported and objective fatigue measures.

TLX↗

NASA NTRS2019

Schedule Factors Associated with the Use of Controlled Rest in a Long-Haul Airline

Controlled Rest (CR) refers to a short, voluntary nap opportunity taken by pilots on the flight deck as a countermeasure to unanticipated sleepiness 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. After merging sleep diary, actigraphy, and schedule data, complete records were analyzed from 240 flights. Sleep was estimated during CR intervals using the Philips Actiware 6.0.9 (Bend, OR) software with wake threshold set to medium. Timing of sleep periods and flight schedules were analyzed relative to home-base time. A mixed-effects binary logistics regression was used to analyze the impact of schedule factors on CR. Preliminary analyses revealed that CR was taken on 45% (n=107) of flights. Average sleep duration within these rest periods was estimated as 24.8 ± 16.1 minutes. CR was more frequent on return flights (arriving at home-base; 58%, n=69) vs. outbound flights (departing from home-base, 31%, n=38; p<0.001). There was no difference for direction of travel (eastbound: 49%, n= 56; westbound: 40%, n= 44; northbound/southbound: 50%, n=7; p=0.272). CR was more frequent on 2-pilot flights (62%, n=81) compared to augmented crew flights (24%, n=26; p<0.001). Of note, 21% (n=23) of augmented flights contained both CR and Bunk Rest. CR was more frequent on flights <10h duration (<10h: 59%, n=78; >10h: 27%, n=29; p<0.001). Flights departing between 12:00h-19:59h (25%, n=23; p<0.026) had the lowest frequency of CR. Data from this airline show that CR is most commonly used as a countermeasure to sleepiness on return, unaugmented, <10h duration, and nighttime flights. The direction of travel did not influence the use of CR. Future studies are required to determine generalizability of these results to other airlines.

Hilditch, Cassie↗

NASA NTRS2019

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.

Food tracker↗

NASA NTRS2019

Distinct Pattern of Oculomotor Impairment Associated with Acute Sleep Loss and Circadian Misalignment

Sleep loss and circadianmisalignment have long been known to impair human cognitive and motor performance with significant societal and health consequences. It is well known that human reaction time to a visual cue is impaired following sleep loss and circadian misalignment, but it has remained unclear how more complex visuomotor control behaviour is altered under these conditions. In this study, we measured 14 parameters of the voluntary ocular tracking response of 12 human participants (six females) to systematically examine the effects of sleep loss and circadianmisalignment using a constant routine 24 h acute sleep-deprivation paradigm. The combination of state-of-the-art oculometric and sleep-research methodologies allowed us to document, for the first time, large changes in many components of pursuit, saccades and visual motion processing as a function of time awake and circadian phase. Further, we observed a pattern of impairment across our set of oculometric measures that is qualitatively different from that observed previously with other mild neural impairments. We conclude that dynamic vision and visuomotor control exhibit a distinct pattern of impairment linked with time awake and circadian phase. Therefore, a sufficiently broad set of oculometric measures could provide a sensitive and specific behavioural biomarker of acute sleep loss and circadian misalignment. We foresee potential applications of such oculometric biomarkers assisting in the assessment of readiness-to-perform higher risk tasks and in the characterization of sub-clinical neural impairment in the face of a multiplicity of potential risk factors, including disrupted sleep and circadian rhythms.

Stone, Leland S.↗

NASA NTRS2019

Low-Dose Caffeine Administration During Acute Sleep Deprivation Eliminates Visual Motion Processing Impairment, but Does Not Improve Saccadic Rate

Oculomotor tracking performance changes according to time awake. A constant routine (CR) study demonstrated that increasing time awake 1) reduces the precision of visual motion processing, 2) decreases steady-state closed-loop pursuit performance and 3) decreases peak saccadic velocity. We aimed to determine the contribution of homeostatic sleep pressure on these oculometric changes by administering low-dose caffeine over one night of sleep deprivation. Participants completed two weeks of at-home 8.5 hours sleep per day, followed by an approximately 24-hour laboratory CR in semi-recumbent posture under less than 4 lux of light. The visual tracking task was performed every two hours after waking and hourly overnight. Low-dose caffeine of 0.3 milligrams per kilogram was administered hourly during the biological night. Nine participants (5F) completed the study. Caffeine dosing: 1) prevented the impairment of visual motion processing, 2) reduced by approximately half the impairment of closed-loop pursuit performance (gain, minus 0.47 percent per hour, significance of slope change: p (probability) less than 0.006; proportion smooth, minus 0.35 percent per hour, p less than 0.005), and 3) had an insignificant (p less than 0.39) effect on the impairment of saccadic peak velocity (slope, minus 1.13 percent per hour; intercept, minus 0.62 percent per hour). These results suggest that visual motion processing and some proportion of closed-loop pursuit performance are impaired due to homeostatic mechanisms during sleep deprivation.

Sleep↗

NASA NTRS2019

The Prevalence of Controlled Rest as a Countermeasure to Sleepiness on the Flight Deck

sleepiness↗

NASA NTRS2018

Increased Dependence on Saccades for Ocular Tracking with Low Dose Alcohol

Previous studies have shown that certain features of oculomotor performance are impaired at or slightly below the legal limit for driving in most U.S. States (0.08% Blood Alcohol Concentration or BAC). Specifically, alcohol impairs saccadic velocity and steady-state tracking at levels between 0.04% and 0.1% BAC. Here we used a suite of standardized oculometric measures to examine the effect of ultra-low levels of alcohol (down to 0.01% BAC) on steady-state tracking. Our high-uncertainty tracking task reveals that the smooth pursuit system is highly sensitive to BAC, with impairmentextrapolating back to BAC levels at or below 0.01%. BAC generates a dose dependent increase in reliance on the saccadic system that maintains overall steady-state tracking effectiveness at least up to 0.08% BAC, albeit with a significant decrease in smoothness.

Tyson, Terence L.↗

NASA NTRS2018

San Francisco Bar Pilot Fatigue Study

The purpose of this study was to evaluate the extent of fatigue among San Francisco Bar Pilots (Maritime Pilots) and its potential impact on safety, and to make recommendations concerning how the risk of fatigue could be managed. Information was gathered via a literature review, observations of Bar Pilots at work, surveys, a task analysis, and an analysis of dispatch records.The work of San Francisco Bar Pilots involves an unusual mix of activities and job demands. Their work calls for situational awareness, reasoning, communication, and perceptual abilities comparable to those required by airline pilots and air traffic controllers. Errors can have severe consequences for public safety and the environment, as well as significant financial costs. Fatigue is increasingly recognized as a hazard that must be managed by the transportation industry. The reduced sleep quality and quantity experienced by personnel who work at night, in conjunction with human circadian rhythms can lead to an operationally significant level of cognitive impairment. The cognitive impact of fatigue includes functions that are critical to safe maritime piloting, such as vigilance, judgment, reaction time and communication. The surveys distributed to Bar Pilots did not uncover evidence of widespread fatigue. The survey results also suggested that fatigue was not a major concern of Bar Pilots. Bar Pilots had overall low scores on the subjective fatigue measures used in the survey, and generally assessed the safety risk due to fatigue as low. Compared to air traffic controllers, Bar Pilots gave significantly lower ratings on questions concerning the prevalence and impact of fatigue. The application of fatigue modeling software to Bar Pilot dispatch records identified that in most cases, pilot's cognitive effectiveness was predicted to be acceptable during their duty periods. However, these results could not be verified with objective data.The study identified a number of fatigue issues that deserve attention. These include Bar Pilot work periods that frequently infringe on the circadian low, consecutive work periods without a significant break, consecutive periods of night work, unpredictable work schedules, start time variability, the potential for sleep inertia, and the number of pilots on the board at any given time.

fatigue↗

NASA NTRS2018

Better Performance on the Psychomotor Vigilance Task Is Associated with Longer Sleep Duration and Lower Self-Reported Sleep Need in the Real World

The psychomotor vigilance task (PVT) is sensitive measure of performance impairment arising from sleep loss and circadian misalignment. Some individuals are able to maintain stable, good performance during laboratory-imposed sleep restriction. It is unclear whether such individuals need less sleep or whether they are more resilient to the effects of sleep loss. We aimed to characterize the relationship between sleep duration and perceived sleep need with PVT performance under real-world conditions.

sleep↗

NASA NTRS2018

Aircraft Exceedances Vary According to Time of Day and Workload

The Flight Operational Quality Assurance (FOQA) programs have been implemented in US and Europe to identify anomalous flights based on data recorded on board an aircraft in an effort to improve flight safety. Numerous methods have been developed to support the analysis of FOQA data. However, it is unclear how FOQA data relates to the performance of the pilot. We sought to characterize the frequency and type of flight exceedances extracted from FOQA data during a controlled pilot schedule in order to determine whether patterns of exceedances related to human control of the aircraft would change according to scheduling factors.

flight data↗

NASA NTRS2017

Oculomotor Behavior Metrics Change According to Circadian Phase and Time Awake

There is a need for non-invasive, objective measures to forecast performance impairment arising from sleep loss and circadian misalignment, particularly in safety-sensitive occupations. Eye-tracking devices have been used in some operational scenarios, but such devices typically focus on eyelid closures and slow rolling eye movements and are susceptible to the intrusion of head movement artifacts. We hypothesized that an expanded suite of oculomotor behavior metrics, collected during a visual tracking task, would change according to circadian phase and time awake, and could be used as a marker of performance impairment.

sleep deprivation↗

NASA NTRS2017

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.

human performance↗

NASA NTRS2016

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.

Flynn-Evans, Erin E.↗

NASA NTRS2016

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.

Caddick, Zachary A.↗

NASA NTRS2016

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.

research↗