Models of selective stimulation with a flat interface nerve electrode for standing neuroprosthetic systems

Area of Science:

• Biomedical Engineering
• Neuroscience
• Rehabilitation Technology

Background:

• Restoring standing function after neurological injury is a significant challenge.
• Selective activation of the femoral nerve is crucial for regaining motor control.
• Current flat interface nerve electrode (FINE) designs lack optimized contact configurations.

Purpose of the Study:

• To determine the optimal number and location of contacts for a FINE.
• To investigate the feasibility of selective fascicular activation in the human femoral nerve.
• To model the electrical stimulation of the femoral nerve using a realistic finite element model.

Main Methods:

• Developed a realistic 3D finite element model of the human femoral nerve and FINE.
• Utilized the McIntyre, Richardson, and Grill (MRG) double-cable axon model.
• Applied simulated voltages as an extracellular field to the nerve model.

Main Results:

• Initial simulations suggest that specific contact configurations may be optimal for individual fascicular groups.
• Achieving acceptable selectivity might necessitate modifications to nerve geometry (nerve reshaping).
• The model provides a framework for evaluating FINE designs.

Conclusions:

• Optimizing FINE contact design is essential for selective femoral nerve stimulation.
• Nerve reshaping could enhance the selectivity of FINE stimulation for functional recovery.
• This research lays the groundwork for advanced neuroprosthetics to restore motor function.