Nuevos métodos para la detección de obstáculos inesperados durante la marcha normal a través de señales EEG

  1. María Elvira 1
  2. Eduardo Iáñez 1
  3. Vicente Quiles 1
  4. Mario Ortiz 1
  5. José M. Azorín 1
  1. 1 Universidad Miguel Hernández de Elche
    info

    Universidad Miguel Hernández de Elche

    Elche, España

    ROR https://ror.org/01azzms13

Libro:
XL Jornadas de Automática: libro de actas. Ferrol, 4-6 de septiembre de 2019
  1. Jose Luis Calvo Rolle (coord.)
  2. Jose Luis Casteleiro Roca (coord.)
  3. María Isabel Fernández Ibáñez (coord.)
  4. Óscar Fontenla Romero (coord.)
  5. Esteban Jove Pérez (coord.)
  6. Alberto José Leira Rejas (coord.)
  7. José Antonio López Vázquez (coord.)
  8. Vanesa Loureiro Vázquez (coord.)
  9. María Carmen Meizoso López (coord.)
  10. Francisco Javier Pérez Castelo (coord.)
  11. Andrés José Piñón Pazos (coord.)
  12. Héctor Quintián Pardo (coord.)
  13. Juan Manuel Rivas Rodríguez (coord.)
  14. Benigno Rodríguez Gómez (coord.)
  15. Rafael Alejandro Vega Vega (coord.)

Editorial: Servizo de Publicacións ; Universidade da Coruña

ISBN: 978-84-9749-716-9

Ano de publicación: 2019

Páxinas: 55-62

Congreso: Jornadas de Automática (40. 2019. Ferrol)

Tipo: Achega congreso

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Resumo

This paper aims to evaluate new methods for detecting the appearance of an unexpected obstacle during the normal gait from electroencephalographic signals (EEG), reducing the false positive rate obtained in previous studies. This way, in case that an emergency occurs, an exoskeleton for both rehabilitation and assistance to people with a motor disability could be stopped. Our purpose is, therefore, to address the implementation of this exoskeleton in real life, getting greater interaction and involvement of the subject with the system. An improvement in the results has been achieved with respect to a previous study, obtaining 75.0 % success rate and 4.5 false positives per minute (FP/min).

Fonte de datos: Dialnet