Abstract
BackgroundMost studies in the field of brain-computer interfacing (BCI) for lower limbs rehabilitation are carried out with healthy subjects, even though insights gained from healthy populations may not generalize to patients in need of a BCI.MethodsWe investigate the ability of a BCI to detect the intention to walk in stroke patients from pre-movement EEG correlates. Moreover, we also investigated how the motivation of the patients to execute a task related to the rehabilitation therapy affects the BCI accuracy. Nine chronic stroke patients performed a self-initiated walking task during three sessions, with an intersession interval of one week.ResultsUsing a decoder that combines temporal and spectral sparse classifiers we detected pre-movement state with an accuracy of 64 % in a range between 18 % and 85.2 %, with the chance level at 4 %. Furthermore, we found a significantly strong positive correlation (r = 0.561, p = 0.048) between the motivation of the patients to perform the rehabilitation related task and the accuracy of the BCI detector of their intention to walk.ConclusionsWe show that a detector based on temporal and spectral features can be used to classify pre-movement state in stroke patients. Additionally, we found that patients’ motivation to perform the task showed a strong correlation to the attained detection rate of their walking intention.
Highlights
Stroke is one of the leading causes of neurological disability among adults and often causes movement impairments [1]
Neurophysiological analysis EEG pre-movement correlates, motor-related cortical potential (MRCP) (0.1 − 1 Hz) and μ band (8 − 13 Hz), were used to assess the intention to walk in all 27 cases (9 subjects x 3 sessions)
Post-hoc comparisons for the MRCP and μ band using the TukeyKramer critical value indicated that the mean score for subject 1 session 2 and 3, subject 4 session 2, subject 6 session 2, subject 7 sessions 1 and 3, subject 9 sessions 1 and were significantly different than the mean of the other subjects (M = −4.36 (0.87), SD = 0.89 (0.47))
Summary
Stroke is one of the leading causes of neurological disability among adults and often causes movement impairments [1]. For patients with motor deficits in lower extremities, gait rehabilitation can improve activities of daily living [2]. A new tendency in rehabilitation is to involve the patient’s body and their brain. This tendency, called “human in the loop”, allows to increase the engagement and motivation of the patients while actively performing the tasks [3]. It has been shown that cortical plasticity of both brain hemispheres contributes to successful gait rehabilitation [4,5,6]. Most studies in the field of brain-computer interfacing (BCI) for lower limbs rehabilitation are carried out with healthy subjects, even though insights gained from healthy populations may not generalize to patients in need of a BCI
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