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Pattern recognition methods for classifying user motion intent based on surface electromyography developed by research groups in well-controlled laboratory conditions are not yet clinically viable for upper limb prosthesis control, due to their limited robustness in users’ real-life situations. To address this problem, a novel postprocessing algorithm, aiming to detect and remove misclassifications...
A structure based finite element analysis (FEA) model can be a means to gain better insight on how surface electromyography (EMG) signals are affected by limb geometry and tissue structures. Beyond that, and to optimize the control of myoelectric prostheses, such models can be used to evaluate signal separation algorithms, or to test the performance of different electrode configurations without the...
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