Vol. 1, Issue 1, Part A (2025)

This study investigates the progressive development of cognitive workload and fatigue among manufacturing workers through an integrated analysis of biomechanical and physiological markers. As modern industrial environments increasingly demand sustained attention, repetitive motions, and physically strenuous activities, there is a growing need for objective measurement tools capable of detecting early signs of performance decline. A sample of manufacturing workers was monitored across an entire work shift using synchronized surface electromyography (sEMG), inertial motion sensors, heart rate variability (HRV) indices, electrodermal activity (EDA), and skin temperature measurements. Subjective workload was assessed using the NASA-TLX scale. The results showed a consistent increase in muscular activation, particularly in the lumbar and upper-limb muscle groups, accompanied by a steady decline in HRV metrics, signifying reduced autonomic recovery and heightened physiological strain. EDA values increased progressively, indicating elevated cognitive activation and arousal, while minor reductions in peripheral skin temperature suggested the onset of fatigue-related vasoconstriction. Significant correlations between sEMG, HRV, EDA, and NASA-TLX scores revealed strong interactions between objective physiological responses and perceived workload. Regression analysis further demonstrated that combined biomechanical and physiological indicators provide a more precise prediction of cognitive fatigue than single-parameter assessment. These findings highlight the value of multimodal monitoring systems for real-time identification of workers at risk of overload, enabling early preventive action. The study emphasizes the need for ergonomic redesign, adaptive break schedules, proactive fatigue management policies, and sensor-based surveillance technologies to enhance worker safety and productivity. By establishing a clear link between physical exertion, autonomic modulation, cognitive arousal, and subjective experience, the research provides a robust framework for improving occupational health practices in manufacturing environments. (indicating biomechanical strain) (HRV) (EDA)