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Autoadaptive neurorehabilitation robotic system assessment with a post-stroke patient

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10.1016/j.riai.2014.11.007
 
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hdl:2117/28330

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Morales Vidal, Ricardo
Badesa Clemente, Francisco Javier
García Aracil, Nicolás
Aranda López, JuanMés informacióMés informacióMés informació
Casals Gelpi, AliciaMés informacióMés informacióMés informació
Document typeArticle
Defense date2015-01-01
Rights accessRestricted access - publisher's policy
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
Abstract
This paper presents a new rehabilitation system that is able to adapt its performance to patient's psychophysiological state during the execution of robotic rehabilitation tasks. Using this approach, the motivation and participation of the patient during rehabilitation activity can be maximized. In this paper, the results of the study with healthy subjects presented in (Badesa et al., 2014b) have been extended for using them with patients who have suffered a stroke. In the first part of the article, the different components of the adaptive system are exposed, as well as a comparison of different machine learning techniques to classify the patient's psychophysiological state between three possible states: stressed, average excitation level and relaxed are presented. Finally, the results of the auto-adaptive system which modifies the behavior of the rehabilitation robot and virtual task in function of measured physiological signals are shown for a patient in the chronic phase of stroke.
CitationMorales, R. [et al.]. Autoadaptive neurorehabilitation robotic system assessment with a post-stroke patient. "Revista iberoamericana de automática e informática industrial", 01 Gener 2015, vol. 12, núm. 1, p. 92-98. 
URIhttp://hdl.handle.net/2117/28330
DOI10.1016/j.riai.2014.11.007
ISSN1697-7912
Publisher versionhttp://www.sciencedirect.com/science/article/pii/S1697791214000867#
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  • Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Articles de revista [1.187]
  • GRINS - Grup de Recerca en Robòtica Intel·ligent i Sistemes - Articles de revista [45]
  • IBEC - Institute for Bioengineering of Catalonia - Articles de revista [50]
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