Advancements in robotics have enabled the creation of prosthetic limbs that are both agile and lightweight. However, many individuals with disabilities are still unable to benefit from these technological advancements. EMG-controlled prosthetics offer a promising solution. To operate, the system must first detect the EMG signal, analyze its features, and decode the user's intention to perform the desired prosthetic motion. A pattern recognition-based system is an effective approach to achieve this goal. This paper explores the identification of basic hand movements for controlling prosthetic hands using s-EMG data.
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Reference paper and Dataset : https://ieeexplore.ieee.org/document/6608802 https://arxiv.org/abs/2107.00733
