Diagnostic Human Fatigue Classification using Wearable Sensors for Intelligent Systems
Published in 2022 17th Annual System of Systems Engineering Conference (SOSE), 2022
Adaptive intelligent systems seek to optimize team performance by adapting to a human teammate. Typically, these adaptations are based on factors known to impact human performance, such as adapting autonomy levels based on human workload. These systems have yet to focus on adapting based on human fatigue; however, fatigue can be just as detrimental to performance as workload. This paper presents a multimodal approach to fatigue classification in order to provide an intelligent system with the necessary information to optimize team performance over long time frames. The results indicate that mental and physical fatigue can be classified accurately for two fatigue levels, but cross-fatigue classification is a more difficult problem.
Recommended citation: L. Nagahanumaiah, S. Singh and J. Heard, “Diagnostic Human Fatigue Classification using Wearable Sensors for Intelligent Systems,” 2022 17th Annual System of Systems Engineering Conference (SOSE), 2022, pp. 424-429.
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