Presentation
Measuring Pilot Fatigue with Subjective, Objective and Physiological Tools
SessionAS2: Physiology
DescriptionTo address concerns regarding operator fatigue for continental flights and other long-term transportation fields, acute sleepiness was induced in participants who then underwent vigilance tasks while seated in a Cessna T37 cockpit for up to four hours. Multiple lighting conditions represented potential flight weather conditions. Collected data included psychomotor vigilance task performance, subjective ratings of sleepiness, and high-resolution electrocardiography (ECG).
Fatigue and stress-related metrics were calculated from the ECG data collected from 21 participants, after extensive processing and filtering of the raw data. These metrics were summarized over 3-minute intervals and combined with performance and subjective data over common time windows. A complex clustering and correlation analysis identified common patterns, within certain groups of participants, which show relationships between some of these measures that can be used to inform fatigue prediction models.
This work highlights how physiological, subjective, and performance-based fatigue assessments correlate in general, and how participants can be characterized according to a small set of common patterns in these correlations. In addition to feeding multivariate fatigue algorithms for aircraft pilots, these results can inform future research that seeks to emphasize unobtrusive and real-time tools to understand operator mental and physical readiness in a variety of fatigue-impacted domains.
Fatigue and stress-related metrics were calculated from the ECG data collected from 21 participants, after extensive processing and filtering of the raw data. These metrics were summarized over 3-minute intervals and combined with performance and subjective data over common time windows. A complex clustering and correlation analysis identified common patterns, within certain groups of participants, which show relationships between some of these measures that can be used to inform fatigue prediction models.
This work highlights how physiological, subjective, and performance-based fatigue assessments correlate in general, and how participants can be characterized according to a small set of common patterns in these correlations. In addition to feeding multivariate fatigue algorithms for aircraft pilots, these results can inform future research that seeks to emphasize unobtrusive and real-time tools to understand operator mental and physical readiness in a variety of fatigue-impacted domains.
Contributor
Event Type
Lecture
TimeTuesday, October 14th11:50am - 12:10pm CDT
LocationGrand Hall I
Aerospace Systems
Human AI Robot Teaming (AI)
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