Human Fatigue Predictions in Complex Aviation Crew Operational Impact Conditions

In this last decade, several regulatory frameworks across the world in all modes of transportation had brought fatigue and its risk management in operations to the forefront. Of all transportation modes air travel has been the safest means of transportation. Still as part of continuous improvement efforts, regulators are insisting the operators to adopt strong fatigue science and its foundational principles to reinforce safety risk assessment and management. Fatigue risk management is a data driven system that finds a realistic balance between safety and productivity in an organization. This work discusses the effects of mathematical modeling of fatigue and its quantification in the context of fatigue risk management for complex global logistics operations. A new concept called Duty DNA is designed within the system that helps to predict and forecast sleep, duty deformations and fatigue. The need for a robust structure of elements to house the components to measure and manage fatigue risk in operations is also debated. By operating on the principles of fatigue management, new science-based predictive, proactive and reactive approaches were designed for an industry leading fatigue risk management program Accurately predicting sleep is very critical to predicting fatigue and alertness. Mathematical models are being developed to track the biological processes quantitatively and predicting temporal profile of fatigue given a person’s sleep history, planned work schedule including night and day exposure. As these models are being continuously worked to improve, a new limited deep learning machine learning based approach is attempted to predict fatigue for a duty in isolation without knowing much of work schedule history. The model within also predicts the duty disruptions and predicted fatigue at the end state of duty

Chronobiol Int

Introduction:Biomathematical models of fatigue (BMMF) predict fatigue during a work-rest schedule on the basis of sleep-wake histories. In the absence of actual sleep-wake histories, sleep-wake histories are predicted directly from work-rest schedules. The predicted sleep-wake histories are then used to predict fatigue. It remains to be determined whether workers organize their sleep similarly across operations and thus whether sleep predictions generalize.Methods:Officers (n = 173) enrolled in the Buffalo Cardio-Metabolic Occupational Police Stress study were studied. Officers\u2019 sleep-wake behaviors were measured using wrist-actigraphy and predicted using a BMMF (FAID Quantum) parameterized in aviation and rail. Sleepiness (i.e. Karolinska Sleepiness Scale (KSS) ratings) was predicted using actual and predicted sleep-wake data. Data were analyzed using sensitivity analyses.Results:During officers\u2019 16.0 \ub1 1.9 days of study participation, they worked 8.6 \ub1 3.1 shifts and primarily worked day shifts and afternoon shifts. Across shifts, 7.0 h \ub1 1.9 h of actual sleep were obtained in the prior 24 h and associated peak KSS ratings were 5.7 \ub1 1.3. Across shifts, 7.2 h \ub1 1.1 h of sleep were predicted in the prior 24 h and associated peak KSS ratings were 5.5 \ub1 1.2. The minute-by-minute predicted and actual sleep-wake data demonstrated high sensitivity (80.4%). However, sleep was observed at all hours-of-the-day, but sleep was rarely predicted during the daytime hours.Discussion:The sleep-wake behaviors predicted by a BMMF parameterized in aviation and rail demonstrated high sensitivity with police officers\u2019 actual sleep-wake behaviors. Additional night shift data are needed to conclude whether BMMF sleep predictions generalize across operations.CC999999/ImCDC/Intramural CDC HHS/United StatesR01 OH009640/OH/NIOSH CDC HHS/United States2020-12-14T00:00:00Z32241186PMC77353948792vault:3627

Why Are Optimistic Entrepreneurs Successful? An Application of the Regulatory Focus Theory

Does entrepreneurial optimism affect business performance? Using a unique data set based on repeated survey design, we investigate this relationship empirically. Our measures of ëoptimismí and ërealismí are derived from comparing the turnover growth expectations of 133 owners-managers with the actual outcomes one year later. Our results indicate that entrepreneurial optimists perform significantly better in terms of profits than pessimists. Moreover, it is the optimist-realist combination that performs best. We interpret our results using regulatory focus theory.http://deepblue.lib.umich.edu/bitstream/2027.42/64399/1/wp914.pd

FIPS: An R Package for Biomathematical Modelling of Human Fatigue Related Impairment

In many workplace contexts, accurate predictions of a human’s fatigue state can drastically improve system safety. Biomathematical models of fatigue (BMMs) are a family of dynamic phenomenological models that predict the neurobehavioural outcomes of fatigue (e.g., sleepiness, performance impairment) based on sleep/wake history (Dawson, Darwent, & Roach, 2017). However, to-date there are no open source implementations of BMMs, and this presents a significant barrier to their broadscale adoption by researchers and industry practitioners. FIPS is an open source R package (R Core Team, 2020) to facilitate BMM research and simulation. FIPS has implementations of several published bio-mathematical models and includes functions for easily manipulating sleep history data into the required data structures. FIPS also includes default plot and summary methods to aid model interpretation. Model objects follow tidy data conventions (Wickham, 2014), enabling FIPS to be integrated into existing research workflows of R users

The sleep of shift workers in a remote mining operation: Methodology for a randomized control trial to determine evidence-based interventions

© Copyright © 2021 Maisey, Cattani, Devine, Lo and Dunican. Shiftwork may adversely impact an individual’s sleep-wake patterns and result in sleep loss ( \u3c 6 h. following night shift), due to the circadian misalignment and the design of rosters and shifts. Within a mining operation, this sleep loss may have significant consequences due to fatigue, including an increased risk of accidents and chronic health conditions. This study aims to (i) determine the efficacy of an intervention that comprises a sleep education program and biofeedback through a smartphone app on sleep quality, quantity, and alertness (ii) determine the prevalence of risk for a potential sleep disorder, and (iii) quantify and describe the sleep habits and behaviors of shift workers in a remote mining operation. This study consists of a randomized controlled trial whereby eighty-eight shift workers within a remote mining operation are randomized to a control group or one of three different treatment groups that are: (i) a sleep education program, (ii) biofeedback on sleep through a smartphone app, or (iii) a sleep education program and biofeedback on sleep through a smartphone app. This study utilizes wrist-activity monitors, biomathematical modeling, and a survey instrument to obtain data on sleep quantity, quality, and alertness. A variety of statistical methods will determine the prevalence of risk for a potential sleep disorder and associations with body mass index, alcohol, and caffeine consumption. A generalized linear mixed model will examine the dependent sleep variables assessed at baseline and post-intervention for the control group and intervention groups, as well as within and between groups to determine changes. The findings from this study will contribute to the current understanding of sleep and alertness behaviors, and sleep problems and disorders amongst shift workers. Importantly, the results may inform fatigue policy and practice on interventions to manage fatigue risk within the mining industry. This study protocol may have a broader application in other shiftwork industries, including oil and gas, aviation, rail, and healthcare

A proposed psychological model of driving automation

This paper considers psychological variables pertinent to driver automation. It is anticipated that driving with automated systems is likely to have a major impact on the drivers and a multiplicity of factors needs to be taken into account. A systems analysis of the driver, vehicle and automation served as the basis for eliciting psychological factors. The main variables to be considered were: feed-back, locus of control, mental workload, driver stress, situational awareness and mental representations. It is expected that anticipating the effects on the driver brought about by vehicle automation could lead to improved design strategies. Based on research evidence in the literature, the psychological factors were assembled into a model for further investigation

Risk of Performance Decrements and Adverse Health Outcomes Resulting from Sleep Loss, Circadian Desynchronization, and Work Overload

Sleep loss, circadian desynchronization, and work overload occur to some extent for ground and flight crews, prior to and during spaceflight missions. Ground evidence indicates that such risk factors may lead to performance decrements and adverse health outcomes, which could potentially compromise mission objectives. Efforts are needed to identify the environmental and mission conditions that interfere with sleep and circadian alignment, as well as individual differences in vulnerability and resiliency to sleep loss and circadian desynchronization. Specifically, this report highlights a collection of new evidence to better characterize the risk and reveals new gaps in this risk as follows: Sleep loss is apparent during spaceflight. Astronauts consistently average less sleep during spaceflight relative to on the ground. The causes of this sleep loss remain unknown, however ground-based evidence suggests that the sleep duration of astronauts is likely to lead to performance impairment and short and long-term health consequences. Further research is needed in this area in order to develop screening tools to assess individual astronaut sleep need in order to quantify the magnitude of sleep loss during spaceflight; current and planned efforts in BHP's research portfolio address this need. In addition, it is still unclear whether the conditions of spaceflight environment lead to sleep loss or whether other factors, such as work overload lead to the reduced sleep duration. Future data mining efforts and continued data collection on the ISS will help to further characterize factors contributing to sleep loss. Sleep inertia has not been evaluated during spaceflight. Ground-based studies confirm that it takes two to four hours to achieve optimal performance after waking from a sleep episode. Sleep inertia has been associated with increased accidents and reduced performance in operational environments. Sleep inertia poses considerable risk during spaceflight when emergency situations necessitate that crewmembers wake from sleep and make quick decisions. A recently completed BHP investigation assesses the effects of sleep inertia upon abrupt awakening, with and without hypnotics currently used in spaceflight; results from this investigation will help to inform strategies relative to sleep inertia effects on performance. Circadian desynchrony has been observed during spaceflight. Circadian desynchrony during spaceflight develops due to schedule constraints requiring non-24 operations or 'slam-shifts' and due to insufficient or mis-timed light exposure. In addition, circadian misalignment has been associated with reduced sleep duration and increased medication use. In ground-based studies, circadian desynchrony has been associated with significant performance impairment and increased risk of accidents when operations coincide with the circadian nadir. There is a great deal of information available on how to manage circadian misalignment, however, there are currently no easily collected biomarkers that can be used during spaceflight to determine circadian phase. Current research efforts are addressing this gap. Work overload has been documented during current spaceflight operations. NASA has established work hour guidelines that limit shift duration, however, schedule creep, where duty requirements necessitate working beyond scheduled work hours, has been reported. This observation warrants the documentation of actual work hours in order to improve planning and in order to ensure that astronauts receive adequate down time. In addition to concerns about work overload, ground based evidence suggests that work underload may be a concern during deep space missions, where torpor may develop and physically demanding workload will be exchanged for monitoring of autonomous systems. Given that increased automation is anticipated for exploration vehicles, fatigue effects in the context of such systems needs to be further understood. Performance metrics are needed to evaluate fitness-for-duty during spaceflight. Although ground-based evidence supports the notion that sleep loss, circadian desynchronization and work overload lead to performance impairment, inconsistency in the measures used to evaluate performance during spaceflight make it difficult to evaluate the magnitude of performance impairment during spaceflight. Work is underway to standardize measures of performance evaluation during spaceflight. Once established, such performance indicators need to be correlated with operational performance. Individual differences in sleep need and circadian preference, phase shifting ability and period have been documented in ground-based studies. Individual differences in response to sleep loss and circadian misalignment have also been documented and are presumed to be associated with genetic polymorphisms. No studies have systematically reported individual differences in sleep or circadian-related outcomes during spaceflight. More work is needed in this area in order to identify genetic or phenotypic biomarkers that predict resilience or vulnerability to sleep loss in order to personalize countermeasure strategies and mitigate performance impairment during spaceflight. Two laboratory and field investigations specific to this topic are currently ongoing; additional efforts, including an effort to mine existing biological data from spaceflight relative to sleep and circadian outcomes, are planned. Sex differences in sleep need and circadian period and phase have been reported in ground-based studies. The impact of these sex differences on performance is unclear. Sex differences in sleep need and circadian rhythms have not been systematically studied during spaceflight, presumably due to the small number of women that have flown in space. More research is needed in this area to evaluate whether any of the observed sex differences in physiology lead to altered performance in spaceflight and on the ground

WHY ARE OPTIMISTIC ENTREPRENEURS SUCCESSFUL? AN APPLICATION OF THE REGULATORY FOCUS THEORY

Does entrepreneurial optimism affect business performance? Using a unique data set based on repeated survey design, we investigate this relationship empirically. Our measures of ‘optimism’ and ‘realism’ are derived from comparing the turnover growth expectations of 133 owners-managers with the actual outcomes one year later. Our results indicate that entrepreneurial optimists perform significantly better in terms of profits than pessimists. Moreover, it is the optimist-realist combination that performs best. We interpret our results using regulatory focus theory.Entrepreneurship, Optimism, Venture Growth, Regulatory Focus Theory, Latvia

Effects of Scheduling on Sleep and Performance in Commercial Motorcoach Operations

Maintaining cognitive alertness during commercial motorcoach operations is important for drivers as they are responsible for preventing, detecting, and managing errors. Schedules that do not follow circadian and homeostatic sleep principles may contribute to fatigue related events and accidents. The Federal Motor Carrier Safety Administration (FMCSA) has hoursof-service (HOS) regulations in place that allow motorcoach operators to work backwardly rotating 18-23 hour duty cycles (a duty cycle being the sum of HOS mandated on and off duty periods), requiring progressively earlier start times. Such schedules do not allow for sufficient and appropriately placed rest periods, resulting in fatigue and decreased performance. This study will investigate the effect of scheduling on sleep and performance in motorcoach operators. We are collecting objective and subjective data on sleep and performance of motorcoach drivers working under the current HOS regulations to observe the prevalence of circadian friendly and mismatched schedules, and the impact work schedules have on sleep and performance. This article describes the study design and methodology