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Combined EEG-fNIRS Decoding of Motor Attempt and Imagery for Brain Switch Control: An Offline Study in Patients With Tetraplegia

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9 Author(s)
Blokland, Y. ; Donders Inst. for Brain, Cognition & Behaviour, Radboud Univ. Nijmegen, Nijmegen, Netherlands ; Spyrou, L. ; Thijssen, D. ; Eijsvogels, T.
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Combining electrophysiological and hemodynamic features is a novel approach for improving current performance of brain switches based on sensorimotor rhythms (SMR). This study was conducted with a dual purpose: to test the feasibility of using a combined electroencephalogram/functional near-infrared spectroscopy (EEG-fNIRS) SMR-based brain switch in patients with tetraplegia, and to examine the performance difference between motor imagery and motor attempt for this user group. A general improvement was found when using both EEG and fNIRS features for classification as compared to using the single-modality EEG classifier, with average classification rates of 79% for attempted movement and 70% for imagined movement. For the control group, rates of 87% and 79% were obtained, respectively, where the “attempted movement” condition was replaced with “actual movement.” A combined EEG-fNIRS system might be especially beneficial for users who lack sufficient control of current EEG-based brain switches. The average classification performance in the patient group for attempted movement was significantly higher than for imagined movement using the EEG-only as well as the combined classifier, arguing for the case of a paradigm shift in current brain switch research.

Published in:

Neural Systems and Rehabilitation Engineering, IEEE Transactions on  (Volume:22 ,  Issue: 2 )

Date of Publication:

March 2014

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