Executive Summary : | Human movement relies heavily on the generation of force from skeletal muscle contractions, which are determined by the central nervous system's processing units. Accurate force estimation is crucial in rehabilitation, prostheses, sports, and clinical diagnostics. Surface electromyography (SEMG) is a non-invasive technique for measuring the electrical activities of contracting skeletal muscles, but the relationship between EMG and force has not been explored well in daily life activities. Developing mathematical models to establish the EMG-force relationship is challenging due to system nonlinearities and intra- and intersubjective muscle dynamics variations. This research aims to develop mathematical models that combine physiological models and kinematic data for force prediction. The models will be adapted to represent muscle physiology and motor neurons, and novel methodological schemes will be employed for predicting force at short intervals. The objectives of this research are to develop models for surface EMG signals generation, establish SEMG-force relations, and validate the models with real-time EMG and force measurements. |