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Predicting changes in performance due to cognitive fatigue: A multimodal approach based on speech motor coordination
Kristin J Heaton1, James R Williamson2, Adam C Lammert3
1Military Performance Division, United States Army Research Institute of Environmental Medicine, Natick, MA, USA.
Objective:
Military job and training activities place significant demands on service members' (SMs') cognitive resources, increasing risk of injury and degrading performance. Early detection of cognitive fatigue is essential to reduce risk and support optimal function. This paper describes a multimodal approach, based on changes in measures of speech motor coordination and electrodermal activity (EDA), for predicting changes in performance following sustained cognitive effort.
Methods:
Twenty-nine active duty SMs completed computer-based cognitive tasks for 2 h (load period). Measures of speech derived from audio were acquired, along with concurrent measures of EDA, before and after the load period. Cognitive performance was assessed before and during the load period using the Automated Neuropsychological Assessment Metrics Military Battery (ANAM MIL). Subjective assessments of cognitive effort and alertness were obtained intermittently.
Results:
Across the load period, participants' ratings of cognitive workload increased, while alertness ratings declined. Cognitive performance declined significantly during the first half of the load period. Three speech and arousal features predicted cognitive performance changes during this period with statistically significant accuracy: EDA (r = 0.43, p = 0.01), articulator velocity coordination (r = 0.50, p = 0.00), and vocal creak (r = 0.35, p = 0.03). Fusing predictions from these features predicted performance changes with r = 0.68 (p = 0.00).
Conclusions:
Results suggest that speech and arousal measures may be used to predict changes in performance associated with cognitive fatigue. This work supports ongoing efforts to develop reliable, unobtrusive measures for cognitive state assessment aimed at reducing injury risk, informing return to work decisions, and supporting diverse mobile healthcare applications in civilian and military settings.
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