Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Abstract

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 wristworn 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 waketime, 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. Video LinkThe video component of this article can be found at https://www.jove.com/video/59851/ Given the differences between laboratory and real-world environments, implementation of strategies and countermeasures developed in the laboratory do not always translate into operations as expected. Individual differences, a broad range of operational work schedules, irregular and unpredictable operations, organizational practices and culture, and labor agreements are some of the factors that can complicate the application of science into practical operational use. As a result, it is important to evaluate the impact of such interventions using consistent and reliable methods to assess sleep, circadian rhythms, fatigue or alertness, and performance. The level of monitoring and data collecting must be kept proportional to the anticipated levels of fatigue and associated risks to safety within an operation 8 . Furthermore, in any safety-sensitive setting, maintaining safe operations is paramount to the investigatory protocol.The gold standard method for a...

Sleep, time, and space—fatigue and performance deficits in pilots, commercial truck drivers, and astronauts

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A rapid, non-invasive method for fatigue detection based on voice information

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

“…The restorative value of sleep, as estimated through subjective fatigue and objective performance, is related to sleep architecture-namely, slow wave sleep (SWS) and rapid eye movement (REM) sleep stages [11,12]. Polysomnography (PSG) is the gold standard to assess sleep stages, but is considered an impractical method for collecting sleep information in operational environments [13]. Consumer sleep trackers cannot measure sleep architecture, but many offer a non-equivalent sleep score under the assumption that sleep stages N1 and N2 are comparable to light sleep, SWS is comparable to deep sleep, and REM is its own category [14][15][16][17].…”