Ankle robotics training with concurrent physiological monitoring in multiple sclerosis: A case report

Abstract

In this paper, we investigate the feasibility of employing robotics, high-density electroencephalography (EEG), and surface electromyography (EMG) for ankle rehabilitation in a subject with multiple sclerosis (MS). A single session of seated, interactive ankle robot (“Anklebot”) training with concurrent 60-channel EEG and 2-channel EMG monitoring was conducted. The task entailed pointing with the ankle while playing a video game that synchronized ankle movements to guide a screen cursor through 560 moving gates. Practice-induced improvements in multiple motor control measures were accompanied by changes in EEG measures of activation and networking, and in EMG measures indicating greater muscle activity. Our results suggest that Anklebot training and concurrent EEG-EMG monitoring is a feasible approach that may be deployed clinically to advance understanding of the neurophysiological mechanisms in motor-learning based recovery in persons with ankle motor deficits secondary to MS and other neurologic injuries.