Effect of Robot-Assisted Training on EEG-Derived Movement-Related Cortical Potentials for Post-Stroke Rehabilitation–A Case Series Study - Maryam Butt (IEEE, 2021)
This paper deploys movement-related cortical potential (MRCP), an electroencephalogram (EEG)-derived time-domain pattern, to assess the effect of robot-assisted motor training in seven post-stroke patients with hand impairment. Patients are divided into two groups of four subjects with supratentorial lesions and a group of three subjects with infratentorial lesions. Both groups participate in multiple-session motor training for their affected hand with an AMADEO rehabilitation robot. During pre- and post-training periods, three assessment procedures which include EEG signals derived from eight specific electrodes, hand-kinematic parameters, and clinical tests are performed. After four weeks of training, the negative peak of the MRCP signals shows a decrease across all electrodes and reaches significance in seven out of the eight electrodes for the first group according to paired t-test ( $p < 0.05$ ). Whereas for the second group, the MRCP signal shows a decrease in its negative peak across all electrodes and reaches significance in two of the eight electrodes (paired t-test, $p < 0.05$ ) after eight weeks. Moreover, these MRCP changes show a positive association with improvements in kinematic parameters and clinical test results for both groups. Hence, this study shows that improvement of clinical outcomes in robot-assisted training is associated with a reduction in the amplitude of the MRCP signal. Furthermore, infratentorial stroke patients show a slower clinical improvement and require longer rehabilitation to produce significant changes in MRCP compared to subjects with supratentorial stroke.