At-home Stroke Rehabilitation System based on Augmented Reality and Brain Computer Interface Paradigm

Abstract

Stroke is the third-leading cause of death and disability combined in the world. The estimated global cost of stroke is over US$721 billion—0.66% of the global GDP. The primary method to induce motor recovery in stroke patients involves active motor training via physical and occupational therapies; however, these treatments are unsatisfactory. Robotics rehabilitation with brain-computer interface (BCI) and virtual reality (VR) can improve the efficacy of therapy as it will involve the active participation of patients’ brains during rehabilitation sessions. Several such systems have been developed; however, the underlying hardware and signal processing algorithms remain challenging. To address these challenges, we propose a radical solution of combining brain-computer interface and augmented reality (AR) into a single rehabilitation platform. We propose to use steady-state visual evoked potentials (SSVEPs) as inputs to the BCI and action observation (AO) implemented via AR-based visual feedback to overcome major limitations of current BCI-based approaches. The proposed BCI-AR-based rehabilitation system has the potential to revolutionize future stroke treatment both in clinics and at home.