Sistema inteligente para la evaluación de movimientos articulares en rehabilitación motora y cognitiva basado en wearables con aplicaciones a servicios de telerehabilitación

  1. Bertomeu-Motos, Arturo 1
  2. Martín, Raúl 1
  3. Lledó Pérez, Luis D. 1
  4. Catalán Orts, José María 1
  5. Blanco Ivorra, Andrea 1
  6. Martínez-Pascual, David 1
  7. García Aracil, Nicolás 1
  1. 1 Universidad Miguel Hernández de Elche
    info

    Universidad Miguel Hernández de Elche

    Elche, España

    ROR https://ror.org/01azzms13

Book:
XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja)
  1. Carlos Balaguer Bernaldo de Quirós (coord.)
  2. José Manuel Andújar Márquez (coord.)
  3. Ramon Costa Castelló (coord.)
  4. Carlos Ocampo Martínez (coord.)
  5. Jesús Fernández Lozano (coord.)
  6. Matilde Santos Peñas (coord.)
  7. José Enrique Simó Ten (coord.)
  8. Montserrat Gil Martínez (coord.)
  9. Jose Luis Calvo Rolle (coord.)
  10. Raúl Marín Prades (coord.)
  11. Eduardo Rocón de Lima (coord.)
  12. Elisabet Estévez Estévez (coord.)
  13. Pedro Jesús Cabrera Santana (coord.)
  14. David Muñoz de la Peña Sequedo (coord.)
  15. José Luis Guzmán Sánchez (coord.)
  16. José Luis Pitarch Pérez (coord.)
  17. Oscar Reinoso García (coord.)
  18. Oscar Déniz Suárez (coord.)
  19. Emilio Jiménez Macías (coord.)
  20. Vanesa Loureiro Vázquez (coord.)

Publisher: Servizo de Publicacións ; Universidade da Coruña

ISBN: 978-84-9749-841-8

Year of publication: 2022

Pages: 87-93

Congress: Jornadas de Automática (43. 2022. Logroño)

Type: Conference paper

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Abstract

This article proposes a novel measurement and evaluation system of the quality of the gestures of the upper extremities. Through three wearable devices, the movements of the joints are estimated and subsequently an OIESGP model classifies the gesture that the subject is executing. Then, the combination of the model prediction with the DTW distance measurement improves the assessment of joint movements, being able to decide the quality of the gesture performed. In this article, the results of upper limb motion assessment with a healthy subject and two stroke patients are shown. The results demonstrate that the fusion of the prediction model, with five joint movements, and the DTW distance offers an intelligent system to evaluate the quality of an executed movement, taking into account each variable independently. At the end of the article, the current status of the patent P202130072 appraisal project that protects the aforementioned system is shown.

Data source: Dialnet