Presentation
Identifying Latent Processes in Multi-Modal Physiological Signals for Team Performance: An Exploratory Structural Equation Modeling Approach
SessionHPM3: Team Performance
DescriptionTeams operating in complex, dynamic environments rely on coordinated interdependent action for mission success. Underlying these team interactions are latent processes that are commonly measured through self-report measures, but little is known about how physiological signals contribute to these latent processes within teaming environments. This study examined how physiological signals from 5-person teams load onto latent factors using exploratory factor analysis (EFA). Results revealed a two-factor structure: inter-beat interval (IBI), respiratory rate, and pupil diameter loaded onto an "arousal" factor, while oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) loaded onto a "cognitive engagement" factor. A structural equation model (SEM) then evaluated whether these factors predicted team and overall individual performance ratings. Arousal significantly predicted both outcomes, whereas cognitive engagement was non-significant. These findings suggest that respiratory and neural activity contribute most distinctly to their respective latent factors, though only arousal serves as a reliable indicator of team and overall individual performance outcomes.
Contributors
Event Type
Lecture
TimeTuesday, October 20th4:50pm - 5:10pm PDT
Location
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