Comput Math Methods Med - Corticomuscular coherence analysis on hand movement distinction for active rehabilitation.

Tópicos

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Resumo

Active rehabilitation involves patient's voluntary thoughts as the control signals of restore device to assist stroke rehabilitation. Although restoration of hand opening stands importantly in patient's daily life, it is difficult to distinguish the voluntary finger extension from thumb adduction and finger flexion using stroke patients' electroencephalography (EMG) on single muscle activity. We propose to implement corticomuscular coherence analysis on electroencephalography (EEG) and EMG signals on Extensor Digitorum to extract their intention involved in hand opening. EEG and EMG signals of 8 subjects are simultaneously collected when executing 4 hand movement tasks (finger extension, thumb adduction, finger flexion, and rest). We explore the spatial and temporal distribution of the coherence and observe statistically significant corticomuscular coherence appearing at left motor cortical area and different patterns within beta frequency range for 4 movement tasks. Linear discriminate analysis is applied on the coherence pattern to distinguish finger extension from thumb adduction, finger flexion, and rest. The classification results are greater than those by EEG only. The results indicate the possibility to detect voluntary hand opening based on coherence analysis between single muscle EMG signal and single EEG channel located in motor cortical area, which potentially helps active hand rehabilitation for stroke patients.

Resumo Limpo

activ rehabilit involv patient voluntari thought control signal restor devic assist stroke rehabilit although restor hand open stand import patient daili life difficult distinguish voluntari finger extens thumb adduct finger flexion use stroke patient electroencephalographi emg singl muscl activ propos implement corticomuscular coher analysi electroencephalographi eeg emg signal extensor digitorum extract intent involv hand open eeg emg signal subject simultan collect execut hand movement task finger extens thumb adduct finger flexion rest explor spatial tempor distribut coher observ statist signific corticomuscular coher appear left motor cortic area differ pattern within beta frequenc rang movement task linear discrimin analysi appli coher pattern distinguish finger extens thumb adduct finger flexion rest classif result greater eeg result indic possibl detect voluntari hand open base coher analysi singl muscl emg signal singl eeg channel locat motor cortic area potenti help activ hand rehabilit stroke patient

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