Impact of task structure on mental fatigue induction and work performance

Area of Science:

• Cognitive Neuroscience
• Human Factors Engineering
• Physiological Monitoring

Background:

• Mental fatigue is a significant risk in safety-critical fields.
• The influence of task structure on mental fatigue progression and physiological responses is not well understood.

Purpose of the Study:

• To investigate how different task structures affect mental fatigue development and its physiological manifestations.
• To evaluate the effectiveness of multimodal physiological signal fusion for continuous fatigue monitoring.

Main Methods:

• 40 participants performed a Stroop task under NORMAL and HALF structures.
• Recorded multimodal physiological data: ECG, EDA, EEG, EOG, RSP, and behavioral performance.
• Utilized LightGBM for five-signal fusion to classify fatigue levels.

Main Results:

• Behavioral changes indicated a shift towards automaticity with accumulating fatigue (reduced RT, lower accuracy).
• Electrodermal activity (EDA) and electrocardiography (ECG) were reliable single-signal fatigue indicators.
• Five-signal fusion achieved high classification performance (F1=0.9186).
• The HALF task structure exhibited attenuated physiological differentiation at higher fatigue levels compared to NORMAL.

Conclusions:

• Task structure significantly modulates mental fatigue dynamics and physiological expression.
• Multimodal physiological signal fusion is a promising approach for robust, continuous fatigue monitoring in high-risk environments.
• Findings contribute to understanding task-structure-dependent fatigue and inform safety protocols.