Muscle Fatigue Management in the Workplace: EMG Monitoring and Active Recovery Strategies

Abstract

This dissertation investigates the impact of varying load intensities on muscle fatigue and the effectiveness of active recovery in mitigating fatigue, employing Electromyography (EMG) monitoring alongside traditional muscle performance assessments. The primary objective is to enhance our understanding of muscle fatigue dynamics, particularly in industrial settings, and to provide insights for optimizing workload management and recovery strategies to improve worker productivity and safety. The research is divided into two main studies. The first study examines the applicability of EMG measures in monitoring muscle fatigue under varying load conditions during dynamic muscle contractions. The results confirm that higher load intensities lead to more pronounced muscle fatigue, as evidenced by significant changes in EMG indicators such as instantaneous Mean Frequency (iMNF) and Root Mean Square (RMS). This study demonstrates the validity of dynamic EMG measurement for real-time monitoring of muscle fatigue, offering a practical tool for environments where load conditions frequently change. The second study focuses on the effects of active recovery following varying load intensities, quantified using both Maximum Voluntary Contraction (MVC) and EMG indicators. The findings indicate that significant load reductions can induce active recovery effects comparable to passive rest. Furthermore, the study develops predictive models for changes in MVC and the duration of active recovery based on EMG indicators, highlighting the potential of continuous EMG monitoring to optimize workload rotations and recovery protocols. Despite these promising findings, the study acknowledges several limitations. The sample size was relatively small and consisted solely of young, healthy male participants, limiting the generalizability of the results. The experimental protocols focused on specific dynamic elbow flexion- extension tasks, which may not fully capture the range of physical activities encountered in real-world settings. Additionally, the post-fatigue tasks were limited to a 4-minute duration, and the study did not include MVC measurements during the fatigue tasks to avoid inducing additional fatigue. The practical applications of this research are significant. Continuous EMG monitoring enables real-time assessment of muscle fatigue, facilitating timely interventions to prevent overexertion and reduce the risk of musculoskeletal disorders. The predictive models developed can inform job rotation strategies, alternating between high- and low-intensity tasks to facilitate active recovery and optimize workload schedules. In athletic settings, EMG monitoring can help design customized training plans that balance high-intensity workouts with appropriate recovery activities, improving performance and reducing injury risks. In conclusion, this dissertation underscores the importance of continuous EMG monitoring in managing muscle fatigue and optimizing recovery strategies. By integrating these methods into industrial and athletic practices, it is possible to enhance safety, productivity, and overall well-being. Future research should address the identified limitations, incorporate more diverse participant cohorts, and explore new applications of EMG technology to further refine and expand its use in various contexts.