HRV-Based Multimodal Physiological Signal Monitoring Using Wearable Biosensors in Human-Computer Interaction: Cognitive Load in Real-Time Strategy Games

基于心率变异性的多模态生理信号监测在人机交互中的应用:利用可穿戴生物传感器监测实时战略游戏中的认知负荷

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Abstract

Real-time strategy (RTS) games provide a cognitively demanding and ecologically valid context for investigating workload dynamics in human-computer interaction (HCI). This multimodal study (HRV, NASA-TLX, behavior, interviews) examined multitasking, visual complexity, and decision pressure in 36 novice RTS players. High multitasking significantly increased subjective workload (total raw-TLX: from 22.50 ± 14.65 to 36.47 ± 20.19, p < 0.001) and prolonged completion time (from 317.17 ± 37.26 s to 354.92 ± 50.70 s, p < 0.001). Decision pressure elevated subjective workload (total raw-TLX: from 20 to 28, p = 0.008) without affecting performance. Although HRV did not consistently differentiate experimental conditions at the group level, it showed stable individual-level associations with perceived workload-both in expected directions (e.g., LF power positively correlated with total raw-TLX across four experiments, r = 0.28-0.53, all p < 0.05) and in inverse relationships that deviate from conventional stress models (e.g., stress index negatively correlated with total raw-TLX, r = -0.34 to -0.40, all p < 0.01). These findings suggest that autonomic responses in complex interactive environments may reflect dynamic engagement processes rather than uniform stress activation, supporting multimodal cognitive load assessment and offering transferable insights for interface design and workload evaluation in demanding HCI contexts.

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