Brain-Computer Interface Controlled Functional Electrical Stimulation: Evaluation With Healthy Subjects and Spinal Cord Injury Patients

This work presents the design, implementation, and feasibility evaluation of a Motor Imagery (MI) based Brain-Computer Interface (BCI) developed to control a Functional Electrical Stimulation (FES) device. The aim of this system is to assist the upper limb motor recovery of patients with spinal cord injury (SCI). With this BCI-controlled FES system, the user performs open and close MI with either the left or right hand, which if detected is used to provide visual feedback and electroestimulation to muscles in the forearm to perform the corresponding grasping movement. The system was evaluated with seven healthy subjects (HS group) and two SCI patients (SC group) in several experimental sessions across different days. Each experimental session consisted of a training routine devoted to collect calibration EEG data to train the BCI machine learning model, and of a validation routine devoted to validate system in online operation. The online system validation showed an accuracy of the recognition of the MI task that ranged between 78% and 81% for HS participants and between 63% and 93% for SCI participants. Additionally, the time taken by the BCI system to trigger the FES device ranged between 7.05 and 7.29 s for HS participants and between 8.43 s and 13.91 s for SCI participants. Finally, significant negative correlations were observed (
$r=-0.418$
,
$p=0.024$
and
$r=-0.437$
,
$p=0.018$
for left and right hand MI conditions, respectively) between the online BCI performance with a quantitative EEG parameter based on event-related desynchronization/synchronization analysis. The results of this work indicate the feasibility of the proposed BCI coupled to a FES device to be used for SCI patients with a moderate level of disability and provides evidence of the functionality of the proposed BCI system in a motor rehabilitation context.