Significance of time awake for predicting pilots' fatigue on short-haul flights: implications for flight duty time regulations.

European regulations restrict the duration of the maximum daily flight duty period for pilots as a function of the duty start time and the number of scheduled flights. However, late duty end times that may include long times awake are not specifically regulated. In this study, fatigue levels in pilots finishing their duty late at night (00:00-01:59 hour) were analysed and compared with pilots starting their duty early (05:00-06:59 hour). Fatigue levels of 40 commercial short-haul pilots were studied during a total of 188 flight duty periods, of which 87 started early and 22 finished late. Pilots used a small handheld computer to maintain a duty and sleep log, and to indicate fatigue levels immediately after each flight. Sleep logs were checked with actigraphy. Pilots on late-finishing flight duty periods were more fatigued at the end of their duty than pilots on early-starting flight duty periods, despite the fact that preceding sleep duration was longer by 1.1 h. Linear mixed-model regression identified time awake as a preeminent factor predicting fatigue. Workload had a minor effect. Pilots on late-finishing flight duty periods were awake longer by an average of 5.5 h (6.6 versus 1.1 h) before commencing their duty than pilots who started early in the morning. Late-finishing flights were associated with long times awake at a time when the circadian system stops promoting alertness, and an increased, previously underestimated fatigue risk. Based on these findings, flight duty limitations should consider not only duty start time, but also the time of the final landing.

Pilot workload during approaches: comparison of simulated standard and noise-abatement profiles.

INTRODUCTION: A new noise-reduced landing approach was tested--a Segmented Continuous Descent Approach (SCDA)-with regard to the resulting workload on pilots. METHODS: Workload of 40 pilots was measured using physiological (heart rate, blood pressure, blink frequency, saliva cortisol concentration) and psychological (fatigue, sleepiness, tension, and task load) parameters. Approaches were conducted in A320 and A330 full-flight simulators during night shift. SCDA was compared to the standard Low Drag Low Power (LDLP) procedure as reference. RESULTS: Mean heart rate and blood pressure during the SCDA were not elevated, but were partly, even significantly, reduced (on average by 5 bpm and 4 mmHg from the flying captain). Cortisol levels did not change significantly with mean values of 0.9 to 1.2 ng ml(-1). Landing was the most demanding segment of both approaches as indicated by significant increases in heart rate and decreases in blink frequency. Subjective task load was low. DISCUSSION: Both approach procedures caused a similar workload level. Interpreting the results, methodological limitations have to be considered, e.g., the artificial and controlled airspace situation in the flight simulator. Nevertheless, it can be concluded that under these ideal conditions, the SCDA is operable without a higher workload for pilots compared to the common LDLP.

An ECG-based algorithm for the automatic identification of autonomic activations associated with cortical arousal.

OBJECTIVES: EEG arousals are associated with autonomic activations. Visual EEG arousal scoring is time consuming and suffers from low interobserver agreement. We hypothesized that information on changes in heart rate alone suffice to predict the occurrence of cortical arousal. METHODS: Two visual AASM EEG arousal scorings of 56 healthy subject nights (mean age 37.0 +/- 12.8 years, 26 male) were obtained. For each of 5 heartbeats following the onset of 3581 consensus EEG arousals and of an equal number of control conditions, differences to a moving median were calculated and used to estimate likelihood ratios (LRs) for 10 categories of heartbeat differences. Comparable to 5 consecutive diagnostic tests, these LRs were used to calculate the probability of heart rate responses being associated with cortical arousals. RESULTS: EEG and ECG arousal indexes agreed well across a wide range of decision thresholds, resulting in a receiver operating characteristic (ROC) with an area under the curve of 0.91. For the decision threshold chosen for the final analyses, a sensitivity of 68.1% and a specificity of 95.2% were obtained. ECG and EEG arousal indexes were poorly correlated (r = 0.19, P <0.001, ICC = 0.186), which could in part be attributed to 3 outliers. The Bland-Altman plot showed an unbiased estimation of EEG arousal indexes by ECG arousal indexes with a standard deviation of +/- 7.9 arousals per hour sleep. In about two-thirds of all cases, ECG arousal scoring was matched by at least one (22.2%) or by both (42.5%) of the visual scorings. Sensitivity of the algorithm increased with increasing duration of EEG arousals. The ECG algorithm was also successfully validated with 30 different nights of 10 subjects (mean age 35.3 [ 13.6 years, 5 male). CONCLUSIONS: In its current version, the ECG algorithm cannot replace visual EEG arousal scoring. Sensitivity for detecting <10-s EEG arousals needs to be improved. However, in a nonclinical population, it may be valuable to supplement visual EEG arousal scoring by this automatic, objective, reproducible, cheap, and time-saving method.