Non-rectangular waveforms for neural stimulation with practical electrodes.

Mesut Sahin, Yanmei Tie

Research output: Contribution to journalArticlepeer-review

101 Scopus citations

Abstract

Historically the rectangular pulse waveform has been the choice for neural stimulation. The strength-duration curve is thus defined for rectangular pulses. Not much attention has been paid to alternative waveforms to determine if the pulse shape has an effect on the strength-duration relation. Similarly the charge injection capacity of neural electrodes has also been measured with rectangular pulses. In this study we questioned if non-rectangular waveforms can generate a stronger stimulation effect, when applied through practical electrodes, by minimizing the neural activation threshold and maximizing the charge injection capacity of the electrode. First, the activation threshold parameters were studied with seven different pulse shapes using computer simulations of a local membrane model. These waveforms were rectangular, linear increase and decrease, exponential increase and decrease, Gaussian, and sinusoidal. The chronaxie time was found to be longer with all the non-rectangular pulses and some provided more energy efficient stimulation than the rectangular waveform. Second, the charge injection capacity of titanium nitride microelectrodes was measured experimentally for the same waveforms. Linearly decreasing ramp provided the best charge injection for all pulse widths tested from 0.02 to 0.5 ms. Finally, the most efficient waveform that maximized the charge injection capacity of the electrode while providing the lowest threshold charge for neural activation was searched. Linear and exponential decrease, and Gaussian waveforms were found to be the most efficient pulse shapes.

Original languageEnglish (US)
Pages (from-to)227-233
Number of pages7
JournalJournal of neural engineering
Volume4
Issue number3
DOIs
StatePublished - Sep 2007

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

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