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Updated: Apr 27, 2026

A Community-based Stress Management Program: Using Wearable Devices to Assess Whole Body Physiological Responses in Non-laboratory Settings
Published on: January 22, 2018
HRV-Based Multimodal Physiological Signal Monitoring Using Wearable Biosensors in Human-Computer Interaction:
Yunlong Shi1, Muyesaier Kuerban1, Yiyang Jin1
1X-Laboratory of Intelligent Interaction (II X-LAB), School of Mechanical Engineering and Automation, Beihang University, 37 Xueyuan Road, Haidian District, Beijing 100191, China.
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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