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A Hybrid Computational Model to Optimize NMES Parameters
Title:
A Hybrid Computational Model to Optimize NMES Parameters
Author:
Arguello, Patrick D., author.
ISBN:
9780438070189
Personal Author:
Physical Description:
1 electronic resource (135 pages)
General Note:
Source: Masters Abstracts International, Volume: 57-06M(E).
Advisors: Deborah S. Won Committee members: Shaurya Agarwal; Ray DeLeon.
Abstract:
Neuromuscular electrical stimulation (NMES) shows promise in restoring a degree 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 afferent (sensory) fibers 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 specific stimulus 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 electrophysiologically accurate model of efferent/afferent fibers 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 micros), low-frequency (30 - 100 Hz) stimulation provides greater activation of sensory axons over motor axons in the context of intramuscular NMES.
Local Note:
School code: 0962
Subject Term:
Added Corporate Author:
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Shelf Number | Item Barcode | Shelf Location | Status |
|---|---|---|---|
| XX(692700.1) | 692700-1001 | Proquest E-Thesis Collection | Searching... |
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