Bio-inspired controller for a dexterous prosthetic hand based on Principal Components Analysis.
Controlling a dexterous myoelectric prosthetic hand with many degrees of freedom (DoFs) could be a very demanding task, which requires the amputee for high concentration and ability in modulating many different muscular contraction signals. In this work a new approach to multi-DoF control is proposed, which makes use of Principal Component Analysis (PCA) to reduce the DoFs space dimensionality and allow to drive a 15 DoFs hand by means of a 2 DoFs signal. This approach has been tested and properly adapted to work onto the underactuated robotic hand named CyberHand, using mouse cursor coordinates as input signals and a principal components (PCs) matrix taken from the literature. First trials show the feasibility of performing grasps using this method. Further tests with real EMG signals are foreseen.
Matrone
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Department of Computer Engineering and Systems Science, University of Pavia, via Ferrata 1, Pavia, Italy. giulia.matrone@unipv.it
Cipriani
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Secco
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Carrozza
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Magenes
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D001186:Artificial Limbs; D001696:Biomechanical Phenomena / Q000502:physiology; D004576:Electromyography; D006225:Hand / Q000502:physiology*; D006801:Humans; D009068:Movement / Q000502:physiology*; D025341:Principal Component Analysis / Q000379:methods*; D014584:User-Computer Interface