Abstract
The loss of the upper limb, especially the hand, can affect the level of autonomy. Developing an effective control system for the upper limb prostheses could improve the quality of users’ life. The aim of this project was to design artificial neural networks for automatic grasp classification. A subset of the grips allowing to perform everyday activities was proposed. The proposed artificial neural networks were evaluated and the maximal accuracy reached 97%.
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The work was supported by the grant 0612/SBAD/3567 funded by the Ministry of Higher Education and Science, Poland.
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Mrozek, A., Sopa, M., Grabski, J.K., Walczak, T. (2023). Controlling of the Upper Limb Prosthesis Using Camera and Artificial Neural Networks. In: Gzik, M., Paszenda, Z., Piętka, E., Tkacz, E., Milewski, K., Jurkojć, J. (eds) Innovations in Biomedical Engineering. Lecture Notes in Networks and Systems, vol 409. Springer, Cham. https://doi.org/10.1007/978-3-030-99112-8_30
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