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- W2897156097 abstract "Prompt detection of movement intention is fundamental to increase the reliability in prostheses control and increase the effectiveness of robotic devices for rehabilitation. A machine learning approach is proposed here to perform activity recognition (overground walking vs rest) using muscles or brain activity. EMG and EEG signals were preprocessed, features in the frequency domain were extracted and the achieved decoding accuracy was around 90%. Although extensive validation is still required, the results constitute a first step towards the goal of predicting gait initiation in real life." @default.
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- W2897156097 date "2018-10-16" @default.
- W2897156097 modified "2023-10-01" @default.
- W2897156097 title "EEG Decoding of Overground Walking and Resting, a Feasibility Study" @default.
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- W2897156097 doi "https://doi.org/10.1007/978-3-030-01845-0_86" @default.
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