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

Abstract : 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.
Type de document :
Communication dans un congrès
The 20th World Congress of the International Federation of Automatic Control, Jul 2017, Toulouse, France
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01491572
Contributeur : Konstantin Akhmadeev <>
Soumis le : vendredi 17 mars 2017 - 10:22:57
Dernière modification le : lundi 10 avril 2017 - 09:36:23

Identifiants

  • HAL Id : hal-01491572, version 1

Collections

Citation

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>

Partager

Métriques

Consultations de la notice

100