Hybrid BCI Coupling EEG and EMG for Severe Motor Disabilities

Rouillard, Jose; Duprès, Alban; Cabestaing, Francois; Leclercq, Stéphanie; Bekaert, Marie-Helene; Piau, Charlotte; Vannobel, Jean-Marc; Lecocq, Claudine

Document type :

Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes

DOI :

10.1016/j.promfg.2015.07.104

Title :

Hybrid BCI Coupling EEG and EMG for Severe Motor Disabilities

Author(s) :

Rouillard, Jose [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Duprès, Alban [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Cabestaing, Francois [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Leclercq, Stéphanie [Auteur]
Bekaert, Marie-Helene [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Piau, Charlotte [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Vannobel, Jean-Marc [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Lecocq, Claudine [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Conference title :

AHFE 2015

City :

Las Vegas

Country :

Etats-Unis d'Amérique

Start date of the conference :

2015-07-26

Publication date :

2015

English keyword(s) :

brain-computer interfaces
hybrid BCI
handicap
virtual reality

HAL domain(s) :

Informatique [cs]/Interface homme-machine [cs.HC]

English abstract : [en]

In this paper, we are studying hybrid Brain-Computer Interfaces (BCI) coupling joystick data, electroencephalogram (EEG – electrical activity of the brain) and electromyogram (EMG – electrical activity of muscles) activities ...
Show more >In this paper, we are studying hybrid Brain-Computer Interfaces (BCI) coupling joystick data, electroencephalogram (EEG – electrical activity of the brain) and electromyogram (EMG – electrical activity of muscles) activities for severe motor disabilities. We are focusing our study on muscular activity as a control modality to interact with an application. We present our data processing and classification technique to detect right and left hand movements. EMG modality is well adapted for DMD patients, because less strength is needed to detect movements in contrast to conventional interfaces like joysticks. Across virtual reality tools, we believe that users will be more able to understand how to interact with such kind of interactive systems. This first part of our study report some very good results concerning the detection of hand movements, according to muscular channel, on healthy subjects.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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