A New Semi-Automatic Approach to Find Suitable Virtual Electrodes in Arrays Using an Interpolation Strategy

Area of Science:

• Rehabilitation Engineering
• Neuroprosthetics
• Biomedical Engineering

Background:

• Functional Electrical Stimulation (FES) utilizes electrode arrays to generate muscle activation.
• Current methods for identifying optimal stimulation parameters can be time-consuming and require significant therapist input.
• Virtual electrodes (VEs) offer dynamic control over stimulation shape, size, and position, but their manual optimization is challenging.

Purpose of the Study:

• To develop and evaluate a feedback-control-assisted manual search strategy for optimizing Virtual Electrode (VE) placement and intensity in FES.
• To enable therapists to efficiently identify effective stimulation areas for multi-degree-of-freedom movements.
• To integrate therapist expertise and patient feedback into the FES parameter selection process.

Main Methods:

• A novel feedback-control-assisted manual search strategy was developed for manipulating VEs.
• The system allows therapists to adjust VE position and intensity while global stimulation intensity is automatically controlled for one degree of freedom.
• The method was tested on four healthy volunteers using a 24-element array to elicit wrist and hand extension.

Main Results:

• The feedback-control-assisted strategy facilitated convenient and continuous modification of VEs by therapists.
• Therapists could focus on optimizing remaining degrees of freedom while the system managed one degree of freedom.
• Successful generation of wrist and hand extension movements was demonstrated in healthy volunteers.

Conclusions:

• The developed method effectively bridges the gap between manual and fully automatic FES parameter identification.
• This approach enhances the efficiency and user-friendliness of optimizing FES for complex movements.
• The strategy holds promise for improving neuroprosthetic control and rehabilitation outcomes.