Complexity-Based Analysis of Skin Conductance-Facial EMG Coupling Under Different Cognitive Loads

This study examined how cognitive load influences the joint dynamics of galvanic skin response (GSR) and facial electromyography (EMG) during graded mental effort. Thirty healthy adults completed four levels of mental-arithmetic tasks while GSR and facial EMG signals were recorded. Signal complexity was quantified using fractal dimension, sample entropy, and approximate entropy. Complexity measures were compared across task conditions, and cross-modal associations between corresponding GSR and EMG measures were evaluated. Across the three metrics, complexity generally increased with task difficulty in both modalities, although the observed changes were more pronounced for GSR than for EMG. Positive associations were also observed between corresponding GSR and EMG complexity measures across the experimental conditions, suggesting coordinated variation in autonomic and somatic responses during increasing cognitive demand. These findings indicate that complexity-based analysis may provide useful information about workload-related changes in electrodermal and facial muscular activity. However, further inferential testing, confidence-interval estimation, and validation in independent samples and real-world settings are required before these measures can be regarded as reliable markers of cognitive workload.