DocumentCode :
1469083
Title :
Efficiency Analysis of Waveform Shape for Electrical Excitation of Nerve Fibers
Author :
Wongsarnpigoon, Amorn ; Woock, John P. ; Grill, Warren M.
Author_Institution :
Biomed. Eng. Dept., Duke Univ., Durham, NC, USA
Volume :
18
Issue :
3
fYear :
2010
fDate :
6/1/2010 12:00:00 AM
Firstpage :
319
Lastpage :
328
Abstract :
Stimulation efficiency is an important consideration in the stimulation parameters of implantable neural stimulators. The objective of this study was to analyze the effects of waveform shape and duration on the charge, power, and energy efficiency of neural stimulation. Using a population model of mammalian axons and in vivo experiments on cat sciatic nerve, we analyzed the stimulation efficiency of four waveform shapes: square, rising exponential, decaying exponential, and rising ramp. No waveform was simultaneously energy-, charge-, and power-optimal, and differences in efficiency among waveform shapes varied with pulse width (PW). For short PWs (≤0.1 ms), square waveforms were no less energy-efficient than exponential waveforms, and the most charge-efficient shape was the ramp. For long PW s (≥ 0.5 ms), the square was the least energy-efficient and charge-efficient shape, but across most PW s, the square was the most power-efficient shape. Rising exponentials provided no practical gains in efficiency over the other shapes, and our results refute previous claims that the rising exponential is the energy-optimal shape. An improved understanding of how stimulation parameters affect stimulation efficiency will help improve the design and programming of implantable stimulators to minimize tissue damage and extend battery life.
Keywords :
bioelectric phenomena; neuromuscular stimulation; prosthetic power supplies; battery life; cat sciatic nerve; charge efficiency analysis; decaying exponential; electrical excitation; energy efficiency analysis; implantable neural stimulator; mammalian axon; nerve fiber; pulse width; rising ramp; stimulation efficiency; waveform shape; Charge efficiency; computational modeling; energy efficiency; implantable stimulators; power efficiency; Algorithms; Animals; Axons; Cats; Computer Simulation; Electric Stimulation; Electrophysiology; Models, Statistical; Nerve Fibers; Nerve Fibers, Myelinated; Sciatic Nerve;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2010.2047610
Filename :
5446391
Link To Document :
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