The investigation of the musculoskeletal system is a challenging task, since comprehensive knowledge of muscle and joint forces within the human body is required.
Therefore, in recent years numerical models have been developed for a better understanding of the musculoskeletal system. Especially for the investigation of long-term effects, the issue of muscle fatigue needs to be taken into consideration in these models.
The objectives of this thesis was to develop a novel EMG based muscle fatigue algorithm and the implementation into a state-of-the-art musculoskeletal modelling system. This included the investigation of the progress of muscle fatigue of single muscles, as well as the behaviour of muscle recruitment pattern when experiencing fatigue.
Therefore, two experimental studies were conducted in the course of this thesis, in order to analyse the progress of muscle fatigue of single muscles in correlation
with relative muscle loadings and to study the behaviour of muscle recruitment pattern of thorax muscles when experiencing fatigue. Based on the results of the first study a fatigue algorithm was developed and implemented to the AnyBody Modeling SystemTM (AMS). Both experimental studies were simulated in the altered AMS to validate the fatigue algorithm and to analyse the behaviour of the
muscle recruitment solver of the modified system.
The results show a good correlation between the simulated muscle fatigue and the experimental data. Furthermore, it revealed a reduction of maximum force capacity of the muscles of about 10-15% compared to the non-fatigued condition.
The analysis of the muscle recruitment pattern indicated an additional activation of muscles in the upper back as well as the abdomen. The numerical simulation of these exercises in the AMS revealed a shift of muscle activity to the upper back
