Analysis of Algorithms for Detection of Pedaling Intention in Brain-Machine Interfaces

The use of brain-machine interfaces in people who has suffered a cerebrovascular accident could help the rehabilitation process through the cognitive involvement of the patient. These interfaces translate the brain waves into commands to control the movement of an assistant mechanical device. Howeve...

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Bibliographic Details
Published in:Revista iberoamericana de automática e informática industrial Vol. 16; no. 2; pp. 222 - 231
Main Authors: M. Ortiz, M. Rodríguez-Ugarte, E. Iáñez, J.M. Azorín
Format: Journal Article
Language:Spanish
Published: Universitat Politècnica de València 01.03.2019
Subjects:
(De)sincronización relacionada a eventos
Análisis y tratamiento de señales
Intención motora
Interfaces Cerebro-Máquina
Máquinas de soporte vectorial
Offline
Rehabilitación
Transformada de Fourier
Transformada de Hilbert-Huang
Transformada de Stoc
ISSN:1697-7912, 1697-7920
Online Access:Get full text
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Summary:The use of brain-machine interfaces in people who has suffered a cerebrovascular accident could help the rehabilitation process through the cognitive involvement of the patient. These interfaces translate the brain waves into commands to control the movement of an assistant mechanical device. However, the control of these devices should be more stable and achieve a higher accuracy. This work studies if algorithms, such as Stockwell or Hilbert-Huang transform, can improve the control of these devices, and if a personalization by subject or electrode configuration is desirable. Besides, through the analysis of five volunteers is determined that the motor intention can not be detected only by data acquired previously to the movement using desynchronized/synchronized related events. Therefore, it is needed to extend the time processing to the two seconds after the movement starting.
ISSN:1697-7912
1697-7920
DOI:10.4995/riai.2018.9861