A Fatigue Involved Modification Framework for Force Estimation in Fatiguing Contraction

To alleviate the negative impacts of muscle fatigue on a force estimation model, a modification framework taking use of fatigue index was put forward in this paper. Muscle force and surface electromyography were first collected using high-density electrode grid and dynamometer. Then, multi-step signal pre-processing and a nonnegative matrix factorization-based signal optimization were conducted, with fatigue indices being extracted in the same time. Next, a degree 4 polynomial fitting model was employed to undertake the training process, and the relationship between the generated model parameters and fatigue indices was built up. In the end, the parameter-index relationship was applied on different testing sets to complete fatigue-modified force estimation. Significant improvement was found in most testing cases across different sexes and ages. Relative decreases of 36.5%, 20.7%, and 20.4% in the percentage root mean square error were achieved by young males, young females, and elderly males. The proposed method can boost the performances of force estimation models, thereby contributing to the development of a variety of fields including biomechanical study, rehabilitation treatment, and prosthesis research.