A brain-computer interface for chronic pain patients using epidural ECoG and visual feedback

Abstract

Electrocorticography (ECoG) offers the possibility of decoding movement intention even in the absence of motor control, making it a powerful signal source for brain-computer interfaces (BCI). We designed a BCI that translates attempts to move the hand into movements of a video of an opening hand to investigate its use for pain therapy and stroke rehabilitation. One patient with phantom limb pain after amputation of the arm and one patient suffering from chronic pain and paralysis after a stroke trained with this BCI for several sessions. Signals were acquired with epidural ECoG grids placed over the motor cortex contralateral to the affected or missing hand. The analysis of data obtained in screening sessions with cued attempted movements showed highly significant (p <; 0.01, permutation test) r2 values for the discrimination between movement and rest conditions for most frequencies up to 200 Hz. Both patients acquired control of the BCI system which was verified by the evaluation of three measures of the ability to start and stop the video application. In particular, both patients learned to reliably start the video application in all trials. This demonstrates that it is feasible for patients with phantom limb pain and chronic pain as well as paralysis after stroke to operate a BCI that targets their missing or impaired limb, making it a potentially useful tool for new approaches in pain therapy and stroke rehabilitation.