FARA
A Fast Artifact Recovery Algorithm with Optimum Stimulation Waveform for Single-Cell Resolution Massively Parallel Neural Interfaces
Rohan Brash (Student TU Delft)
Wouter Serdijn (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Dante G. Muratore (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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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.