The use of biosignal based neurofeedback for reinforcing the motor recovery process during post-stroke rehabilitation is becoming increasingly popular in recent years. A popular technology in providing relevant neurofeedback is the brain-computer interfaces (BCI) which is generally powered by electroencephalographic (EEG) signals in the brain as this is non-invasive and safe to use. However, the connection between the brain and the muscle signals is not yet fully explored for rehabilitation purpose, despite being proved as a biomarker for motor recovery. Studies have shown that corticomuscular coherence (CMC) is a reliable measure of interaction between brain and muscle activity. However, CMC is very difficult estimate in real-time with sufficient accuracy as it requires a long duration time series to get a stable response. This makes the scope of a CMC based BCI limited for reinforcing the brain-muscle interaction during neurofeedback which may hinder motor recovery.
In order to remove such limitations, we developed a new method called correlation between band-limited power time courses (CBPT), which is capable of providing real-time neurofeedback based on the corticomuscular interaction in real-time with high accuracy. The experiment was done both on healthy individuals and hemiparetic stroke patients while the online neurofeedback was provided by CBPT and the CMC was analysed offline for comparing the accuracy between the two. Results showed that the classification accuracy was significantly high for both the healthy and patient groups in favor of CBPT.
CBPT was a better option compared to the use of cortico-muscular coherence. Also, with CBPT, in the course of a task execution to evaluate the interaction between EEG and EMG, the change in activity is more important than the magnitude of EMG activity. The difference between the features of CBPT in healthy participants and patients during a particular task is an indication that there is still a similarity between cortico-muscular coherence and CBPT. Despite this, CBPT still has an edge over cortico-muscular coherence especially when accuracies are concerned and would be a more viable option for robotic neurorehabilitation processes. The work is published in the peer-reviewed journal, Journal of Neuroscience Methods. Further study will investigate the suitability of CBPT as a biomarker for monitoring the motor recovery.
Chowdhury, A., Raza, H., Meena, Y.K., Dutta, A., and Prasad, G. An EEG-EMG correlation based brain-computer interface for hand orthosis supported neuro-rehabilitation, Journal of Neuroscience Methods 312 (2019) 1–11Go To Journal of Neuroscience Methods