Thesis

A Hybrid Computational Model to Optimize NMES Parameters

Neuromuscular electrical stimulation (NMES) shows promise in restoring a de- gree of ambulatory function in patients who have sustained spinal cord injury (SCI). These therapeutic effects are enabled via stimulation of both the efferent (motor) or af- ferent (sensory) bers found in the peripheral nervous system. It has been shown that by changing stimulus parameters, the efferent or afferent pathways could be activated preferentially. Several studies have been published demonstrating the specic stimu- lus parameters required to preferentially activate the afferent pathway. Most of these studies, however, utilize surface electrodes, with little research done on percutaneous stimulation involving implanted microelectrodes. By developing an electrophysiolog- ically accurate model of efferent/afferent bers as well as that of the microelectrode, we hope to identify the optimal stimulus parameters for aerent ber recruitment in our NMES-based therapy. Our simulations reveal that short pulsewidth (50 s), low-frequency (30 - 100 Hz) stimulation provides greater activation of sensory axons over motor axons in the context of intramuscular NMES. iv

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