Electromyographic driven assisted therapy for hand rehabilitation by robotic orthosis and artificial neural networks

Julian Ramirez, Mariel Alfaro, Isaac Chairez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

This study addressed the design, construction and instrumentation of an active hand orthosis driven by electromyographic (EMG) signals captured over the arm. The EMG signals were classified using a static neural network (SNN) supplied by the momentum learning scheme. The orthosis was actuated with a collection of direct current motor commanded by distributed control strategy based on the so-called twisting controller. The orthosis was interfaced to a computer where a special class of graphic user interface (GUI) was implemented. This GUI contains a sequence of suggested exercises that patient wearing the orthosis must try to develop. The orthosis was implemented and the proposed controller forced the tracking of the reference trajectories supplied by the GUI. The orthosis was evaluated in simulation to adjust the EMG signal classifier as well as the controller gains. A real orthosis was constructed and controlled using the gains obtained at the simulation stage.

Idioma originalInglés
Título de la publicación alojadaVI Latin American Congress on Biomedical Engineering, CLAIB 2014
EditoresAriel Braidot, Alejandro Hadad
EditorialSpringer Verlag
Páginas75-78
Número de páginas4
ISBN (versión digital)9783319131160
DOI
EstadoPublicada - 2015
Evento6th Latin American Congress on Biomedical Engineering, CLAIB 2014 - Paraná, Argentina
Duración: 29 oct. 201431 oct. 2014

Serie de la publicación

NombreIFMBE Proceedings
Volumen49
ISSN (versión impresa)1680-0737

Conferencia

Conferencia6th Latin American Congress on Biomedical Engineering, CLAIB 2014
País/TerritorioArgentina
CiudadParaná
Período29/10/1431/10/14

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