The instability of myoelectric signals over time complicates their use to control poly-articulated prosthetic hands. To address this problem, studies have tried to combine surface electromyography with modalities that are less affected by the amputation and the environment, such as accelerometry...
04b Atto di convegno in volume
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The application of machine learning to recognize hand movements from surface electromyography has led to promising academic results. Unfortunately, it has proven difficult to translate these results in better control methods for the end-users of upper-limb prostheses. Recent studies have pointed...
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During the past 60 years scientific research proposed many techniques to control robotic hand prostheses with surface electromyography (sEMG). Few of them have been implemented in commercial systems also due to limited robustness that may be improved with multimodal data. This paper presents the...
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Domain adaptation methods have been proposed to reduce the training efforts needed to control an upper-limb prosthesis by adapting well performing models from previous subjects to the new subject. These studies generally reported impressive reductions in the required number of training samples to...
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