EEG-Controlled Functional Electrical Stimulation Therapy With Automated Grasp Selection: A Proof-of-Concept Study

Area of Science:

• Neuroscience
• Rehabilitation Engineering
• Biomedical Engineering

Background:

• Functional electrical stimulation therapy (FEST) shows promise for restoring upper extremity function post-cervical spinal cord injury (SCI).
• Existing FEST systems can be enhanced by integrating voluntary movement attempts and varied functional grasp practice.

Purpose of the Study:

• To describe and evaluate a novel FEST system incorporating brain-computer interface (BCI) and computer vision (CV) modules.
• To facilitate voluntary movement attempts and massed practice of functional grasp in individuals with SCI.

Main Methods:

• An EEG-based BCI with a single electrode detected movement initiation attempts.
• A CV system identified target objects and selected appropriate grasp types (precision, lateral, palmar, lumbrical).
• The system was tested on neurologically intact participants and one individual with complete cervical SCI.

Main Results:

• An integrated BCI-CV-FES system was successfully demonstrated.
• The CV module achieved 90.8% classification accuracy across eight objects.
• Average BCI latency for movement trigger was 5.9 ± 1.5 seconds.

Conclusions:

• BCI and CV can be integrated into FEST systems cost-effectively and with minimal setup.
• This clinically relevant system promotes voluntary movement and diverse grasp repetitions during FEST.
• The technology offers a promising avenue for SCI rehabilitation.