Sequential estimation of intramuscular EMG model parameters for prosthesis control
| Autor: | Monsifrot, Jonathan, Le Carpentier, Eric, Farina, Dario, Aoustin, Yannick |
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| Přispěvatelé: | Institut de Recherche en Communications et en Cybernétique de Nantes (IRCCyN), Mines Nantes (Mines Nantes)-École Centrale de Nantes (ECN)-Ecole Polytechnique de l'Université de Nantes (EPUN), Université de Nantes (UN)-Université de Nantes (UN)-PRES Université Nantes Angers Le Mans (UNAM)-Centre National de la Recherche Scientifique (CNRS), Department of Neurorehabilitation Engineering, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen (UMG) |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: | |
| Zdroj: | IEEE/RSJ International Conference on Intelligent Robots and Systems, Workshop on Robotics for Neurology and Rehabilitation IEEE/RSJ International Conference on Intelligent Robots and Systems, Workshop on Robotics for Neurology and Rehabilitation, Sep 2011, San Francisco, Ca |
| Popis: | International audience; EMG signals are an image of the control from the central nervous system transmitted to muscles. Intramuscular EMG signals are collected directly in muscles. The collected data contain information on the neural control of the muscle. This information can be used for controlling external devices (myo- electric control), however realtime processing of intramuscular EMG signals is complex. The aim of this paper is to present a sequential method to estimate parameters which can lead to an active drive of an upper limb prosthesis. A system model will be presented and then an algorithm detailed. Results of the proposed algorithm applied to simulated and experimental data will be discussed. |
| Databáze: | OpenAIRE |
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