Literature DB >> 20388602

Efficiency analysis of waveform shape for electrical excitation of nerve fibers.

Amorn Wongsarnpigoon1, John P Woock, Warren M Grill.   

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 (< or = 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 (> or = 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.

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Year:  2010        PMID: 20388602      PMCID: PMC3071515          DOI: 10.1109/TNSRE.2010.2047610

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  21 in total

1.  Effect of stimulus (postsynaptic current) shape on fibre excitation.

Authors:  N A Dimitrova; G V Dimitrov
Journal:  Gen Physiol Biophys       Date:  1992-02       Impact factor: 1.512

2.  Charge density and charge per phase as cofactors in neural injury induced by electrical stimulation.

Authors:  D B McCreery; W F Agnew; T G Yuen; L Bullara
Journal:  IEEE Trans Biomed Eng       Date:  1990-10       Impact factor: 4.538

3.  Stimulation with minimum power.

Authors:  F OFFNER
Journal:  J Neurophysiol       Date:  1946-09       Impact factor: 2.714

4.  Non-rectangular waveforms for neural stimulation with practical electrodes.

Authors:  Mesut Sahin; Yanmei Tie
Journal:  J Neural Eng       Date:  2007-05-02       Impact factor: 5.379

5.  Analysis of the quasi-static approximation for calculating potentials generated by neural stimulation.

Authors:  Chad A Bossetti; Merrill J Birdno; Warren M Grill
Journal:  J Neural Eng       Date:  2007-12-17       Impact factor: 5.379

6.  Axons, but not cell bodies, are activated by electrical stimulation in cortical gray matter. I. Evidence from chronaxie measurements.

Authors:  L G Nowak; J Bullier
Journal:  Exp Brain Res       Date:  1998-02       Impact factor: 1.972

7.  Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle.

Authors:  Cameron C McIntyre; Andrew G Richardson; Warren M Grill
Journal:  J Neurophysiol       Date:  2002-02       Impact factor: 2.714

8.  Experimental nondestructive electrical stimulation of the brain and spinal cord.

Authors:  J T Mortimer; C N Shealy; C Wheeler
Journal:  J Neurosurg       Date:  1970-05       Impact factor: 5.115

9.  Optimization of neural stimuli based upon a variable threshold potential.

Authors:  D Dean; P D Lawrence
Journal:  IEEE Trans Biomed Eng       Date:  1985-01       Impact factor: 4.538

10.  Differences among implanted pulse generator waveforms cause variations in the neural response to deep brain stimulation.

Authors:  Christopher R Butson; Cameron C McIntyre
Journal:  Clin Neurophysiol       Date:  2007-06-19       Impact factor: 3.708

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  23 in total

1.  What Can be Learned from the Time Course of Changes in Low-Frequency Stimulated Muscle?

Authors:  Dirk Pette
Journal:  Eur J Transl Myol       Date:  2017-06-24

2.  Predicting myelinated axon activation using spatial characteristics of the extracellular field.

Authors:  E J Peterson; O Izad; D J Tyler
Journal:  J Neural Eng       Date:  2011-07-13       Impact factor: 5.379

3.  Numerical optimization of coordinated reset stimulation for desynchronizing neuronal network dynamics.

Authors:  Shigeru Kubota; Jonathan E Rubin
Journal:  J Comput Neurosci       Date:  2018-06-07       Impact factor: 1.621

4.  A model of motor and sensory axon activation in the median nerve using surface electrical stimulation.

Authors:  Jessica L Gaines; Kathleen E Finn; Julia P Slopsema; Lane A Heyboer; Katharine H Polasek
Journal:  J Comput Neurosci       Date:  2018-06-26       Impact factor: 1.621

Review 5.  The development and modelling of devices and paradigms for transcranial magnetic stimulation.

Authors:  Stefan M Goetz; Zhi-De Deng
Journal:  Int Rev Psychiatry       Date:  2017-04-26

6.  Muscle Decline in Aging and Neuromuscular Disorders - Mechanisms and Countermeasures: Terme Euganee, Padova (Italy), April 13-16, 2016.

Authors: 
Journal:  Eur J Transl Myol       Date:  2016-03-31

7.  Neural selectivity, efficiency, and dose equivalence in deep brain stimulation through pulse width tuning and segmented electrodes.

Authors:  Collin J Anderson; Daria Nesterovich Anderson; Stefan M Pulst; Christopher R Butson; Alan D Dorval
Journal:  Brain Stimul       Date:  2020-04-09       Impact factor: 8.955

8.  Stimulation Efficiency With Decaying Exponential Waveforms in a Wirelessly Powered Switched-Capacitor Discharge Stimulation System.

Authors:  Hyung-Min Lee; Bryan Howell; Warren M Grill; Maysam Ghovanloo
Journal:  IEEE Trans Biomed Eng       Date:  2017-08-17       Impact factor: 4.538

9.  Energy-efficient waveform shapes for neural stimulation revealed with a genetic algorithm.

Authors:  Amorn Wongsarnpigoon; Warren M Grill
Journal:  J Neural Eng       Date:  2010-06-23       Impact factor: 5.379

10.  Evaluation of novel stimulus waveforms for deep brain stimulation.

Authors:  Thomas J Foutz; Cameron C McIntyre
Journal:  J Neural Eng       Date:  2010-11-17       Impact factor: 5.379

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