Análisis de Algoritmos para Detección de Pedaleo en Interfaces Cerebro-Máquina

M. Ortiz, M. Rodríguez-Ugarte, E. Iáñez, J.M. Azorín

Resumen

El uso de interfaces cerebro-máquina en personas que han sufrido un accidente cerebro-vascular puede ayudar en su proceso de rehabilitación mediante la implicación cognitiva del paciente. Dichas interfaces traducen las ondas cerebrales en comandos con el fin de controlar un dispositivo mecánico de movimiento asistido. No obstante, el control de estos dispositivos debería ser más robusto y tener una alta precisión. Este trabajo estudia si algoritmos basados en transformadas como las de Stockwell o Hilbert-Huang pueden mejorar el control de estos dispositivos aumentando su precisión, y si es recomendable llevar a cabo una personalización por sujeto y configuración de electrodos. Mediante el análisis de cinco voluntarios se comprueba además, que no es posible detectar con suficiente robustez la intención motora a partir de la desincronización/sincronización relacionada a eventos motores con únicamente los datos previos al movimiento. Por ello, es preciso extender el tiempo de análisis a los dos segundos posteriores al inicio del movimiento.


Palabras clave

Análisis y tratamiento de señales; (De)sincronización relacionada a eventos; Intención motora; Interfaces Cerebro-Máquina; Máquinas de soporte vectorial; Offline; Rehabilitación; Transformada de Fourier; Transformada de Hilbert-Huang; Transformada de Stoc

Clasificación por materias

Filtrado, estimación y análisis y tratamiento de señales e imágenes

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