FARA

A Fast Artifact Recovery Algorithm with Optimum Stimulation Waveform for Single-Cell Resolution Massively Parallel Neural Interfaces

Conference Paper (2022)
Author(s)

Rohan Brash (Student TU Delft)

Wouter Serdijn (TU Delft - Bio-Electronics)

Dante G. Muratore (TU Delft - Bio-Electronics)

Research Group
Bio-Electronics
Copyright
© 2022 Rohan Brash, W.A. Serdijn, D.G. Muratore
DOI related publication
https://doi.org/10.1109/ISCAS48785.2022.9937814
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Rohan Brash, W.A. Serdijn, D.G. Muratore
Research Group
Bio-Electronics
Pages (from-to)
190-194
ISBN (print)
978-1-6654-8486-2
ISBN (electronic)
978-1-6654-8485-5
Reuse Rights

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Abstract

This paper introduces a fast artifact recovery algorithm (FARA) that uses electrochemical impedance spectroscopy to model the electrode-tissue interface and design an optimum stimulation waveform to minimize the residual artifact duration in single-cell resolution neural interfaces. Results in saline solution with a custom PCB and a 30 $\mu \mathrm{m}$ diameter microelectrode array show a worst case artifact recovery time of 160 $\mu \mathrm{s}$ when measured from the end of the working phase (anodic 500 $\mathrm{n}\mathrm{A}, 250\mu \mathrm{s})$. On average, the proposed algorithm provides an 81% improvement over a triphasic charge-balanced stimulation waveform.

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