Comparing Kolmogorov-Arnold Networks and Conventional Machine Learning Algorithms for sEMG Based Movement Classification
Myoelectric prosthetics utilize machine learning(ML) algorithms to translate surface electromyography(sEMG) signal patterns into movement, allowing patients to easily control their prosthesis. While the use of conventional ML algorithms has been effective within these prosthetics, challenges still remain in terms of classification accuracy and computation speed. It was hypothesized that Kolmogorov