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Residual Voltage in Biphasic Electrical Stimulation: Cause, Clues, and Control

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posted on 2016-02-04, 00:00 authored by Ashwati KrishnanAshwati Krishnan

Electrical stimulation of neural tissue has been known to evoke functional responses in animals. Stimulation is primarily performed by passing controlled, symmetric biphasic current pulses to an electrode placed near the neural tissue. The biphasic current pulse consists of a negative pulse, followed by a positive pulse to maintain charge neutrality. A theoretical analysis on a first order electrode-electrolyte (tissue) interface model has shown that perfectly balanced input current signals do not ensure net neutrality at the interface, due to an unrecoverable loss of charge via the faradaic impedance. In chronically implanted devices, there is currently no practical way to quickly identify changes that occur at the electrode-tissue interface, especially in high-density electrode arrays. This work explores the extent to which the residual voltage can act as a preliminary indicator of electrode degradation, because residual voltage is essentially a characteristic of the interface. While residual voltage provides timely feedback when sampled at regular intervals, it can accumulate and a DC voltage on a stimulation electrode can be potentially unsafe in a chronically implanted device. The method of delivering current signals has traditionally been implemented as an open loop system. This work also demonstrates that one can control the residual voltage by correcting the positive pulse of the biphasic signal based on the existing state of the electrode-electrolyte/tissue interface. While the resulting biphasic stimulation waveform is imbalanced, the interface is electrochemically neutral. The updated value of the imbalanced anodic pulse width can provide us meta-data about the interface, in case there is any degradation. By controlling the residual voltage at the electrode actively with feedback, the proposed closed loop system will improve the safety of neural stimulator systems.

History

Date

2016-02-04

Degree Type

  • Dissertation

Department

  • Electrical and Computer Engineering

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

Shawn K. Kelly

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