dariaomelkina/bionics_project
Course project for the Signal Processing and AI courses at UCU.
This project helps bionic prosthetic developers understand and classify specific arm movements from raw electromyographic (EMG) signals. It takes raw myoelectric data, processes it to remove noise, extracts key features, and then predicts intended hand movements like opening/closing or gripping. Biomedical engineers and researchers working on bionic limb control systems would find this useful for developing and testing their algorithms.
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Use this if you are a biomedical engineer or researcher needing to process raw EMG signals and classify specific upper limb movements for bionic prosthetic development.
Not ideal if you are working with other types of biomedical signals, lower limb prosthetics, or require real-time control applications without further optimization.
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Jan 18, 2022
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