English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/103659
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Exportar a otros formatos:

Title

A multimodal human–robot interface to drive a neuroprosthesis for tremor management

AuthorsGallego, Juan Álvaro CSIC ORCID CVN; Ibáñez Pereda, Jaime CSIC ORCID ; Dideriksen, Jakob L.; Serrano, José Ignacio CSIC ORCID CVN; Castillo Sobrino, María Dolores del; Farina, Dario; Rocón, Eduardo CSIC ORCID
Issue DateNov-2012
CitationSystems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Series42 (6)
1159-1168
AbstractTremor is the most prevalent movement disorder, and its incidence is increasing with aging. In spite of the numerous therapeutic solutions available, 65% of those suffering from upper limb tremor report serious difficulties during their daily living. This gives rise to research on different treatment alternatives, amongst which wearable robots that apply selective mechanical loads constitute an appealing approach. In this context, the current work presents a multimodal human-robot interface to drive a neuroprosthesis for tremor management. Our approach relies on the precise characterization of the tremor to modulate a functional electrical stimulation system that compensates for it. The neuroprosthesis is triggered by the detection of the intention to move derived from the analysis of electroencephalographic activity, which provides a natural interface with the user. When a prediction is delivered, surface electromyography serves to detect the actual onset of the tremor in the presence of volitional activity. This information in turn triggers the stimulation, which relies on tremor parameters-amplitude and frequency-derived from a pair of inertial sensors that record the kinematics of the affected joint. Surface electromyography also yields a first characterization of the tremor, together with precise information on the preferred stimulation site. Apart from allowing for an optimized performance of the system, our multimodal approach permits the implementation of redundant methods to both enhance the reliability of the system and adapt to the specific needs of different users. Results with a representative group of patients illustrate the performance of the interface presented here and demonstrate its feasibility.
URIhttp://hdl.handle.net/10261/103659
DOIhttp://dx.doi.org/10.1109/TSMCC.2012.2200101
Appears in Collections:(CAR) Artículos
Files in This Item:
File Description SizeFormat 
gallego_et_al_TSMC-C.pdf1,19 MBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 

Related articles:


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.