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Auto-adaptive robot-aided therapy using machine learning techniques

Autor
Badesa, F.; Morales, R.; García Aracil, Nicolás; Sabater, J.; Casals, A.; Zollo, L.
Tipus d'activitat
Article en revista
Revista
Computer methods and programs in biomedicine
Data de publicació
2014-09
Volum
116
Número
2
Pàgina inicial
123
Pàgina final
130
DOI
https://doi.org/10.1016/j.cmpb.2013.09.011 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0169260713003180 Obrir en finestra nova
Resum
This paper presents an application of a classification method to adaptively and dynamically modify the therapy and real-time displays of a virtual reality system in accordance with the specific state of each patient using his/her physiological reactions. First, a theoretical background about several machine learning techniques for classification is presented. Then, nine machine learning techniques are compared in order to select the best candidate in terms of accuracy. Finally, first experimenta...
Paraules clau
Multimodal interfaces, Physiological state, Rehabilitation robotics, Stroke rehabilitation
Grup de recerca
CREB - Centre de Recerca en Enginyeria Biomedica
GRINS - Grup de Recerca en Robòtica Intel·ligent i Sistemes

Participants

  • Badesa Clemente, Francisco Javier  (autor)
  • Morales Vidal, Ricardo  (autor)
  • García Aracil, Nicolás  (autor)
  • Sabater Navarro, José Mª  (autor)
  • Casals Gelpi, Alicia  (autor)
  • Zollo, Loredana  (autor)