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Communication Dans Un Congrès Année : 2017

A testing system for a real-time gesture classification using surface EMG

Résumé

This study addresses the development of a testing system for pattern-recognition- based strategies of myoelectric control. This text describes the structure and components of the proposed system, as well as a process of its testing. The latter included an acquisition of an accompanying EMG, using MyoTM armband by Thalmic Labs Inc.TM, for six different gestures (classes) from seven subjects, as well as its processing, feature extraction, training the classifier and further real-time validation. The results show that system provides acceptable classification rates.
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Dates et versions

hal-01491572 , version 1 (17-03-2017)

Identifiants

  • HAL Id : hal-01491572 , version 1

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Konstantin Akhmadeev, Elena Rampone, Tianyi Yu, Yannick Aoustin, Eric Le Carpentier. A testing system for a real-time gesture classification using surface EMG. The 20th World Congress of the International Federation of Automatic Control, Jul 2017, Toulouse, France. ⟨hal-01491572⟩
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