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http://hdl.handle.net/2183/23661 Nuevos métodos para la detección de obstáculos inesperados durante la marcha normal a través de señales EEG
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Elvira, María
Iáñez, Eduardo
Quiles, Vicente
Ortiz, Mario
Azorín, José M.
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Elvira, M., Iáñez, E., Quiles, V., Ortiz, M., Azorín, J.M. (2019). Nuevos métodos para la detección de obstáculos inesperados durante la marcha normal a través de señales EEG. En XL Jornadas de Automática: libro de actas, Ferrol, 4-6 de septiembre de 2019 (pp. 55-62). DOI capítulo: https://doi.org/10.17979/spudc.9788497497169.055. DOI libro: https://doi.org/10.17979/spudc.9788497497169
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[Resumen] El objetivo del presente trabajo es evaluar nuevos métodos que permitan detectar la aparición de un obstáculo inesperado durante la marcha normal a partir de señales electroencefalográficas (EEG), reduciendo la tasa de falsos positivos obtenida en estudios previos. De esta forma, se podría detener en caso de emergencia un exoesqueleto destinado tanto a tareas de rehabilitación como de asistencia a personas con alguna discapacidad motora. Se pretende así ir aproximándonos a una implementación de este en la vida real, consiguiendo una mayor interacción e implicación del sujeto con el sistema. Se ha conseguido una mejora en los resultados obtenidos respecto a un estudio previo, obteniendo un 75.0% de acierto y 4.5 falsos positivos por minuto (FP/min).
[Abstract] 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).
[Abstract] 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).
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