English

HermEIS: A Parallel Multichannel Approach to Rapid Spectral Characterization of Neural MEAs

Signal Processing 2024-03-13 v1

Abstract

The promise of increasing channel counts in high density (>104> 10^4) neural Microelectrode Arrays (MEAs) for high resolution recording comes with the curse of developing faster characterization strategies for concurrent acquisition of multichannel electrode integrities over a wide frequency spectrum. To circumvent the latency associated with the current multiplexed technique for impedance acquisition, it is common practice to resort to the single frequency impedance measurement (i.e. Z1kHzZ_{1 \text{kHz}}). This, however, does not offer sufficient spectral impedance information crucial for determining the capacity of electrodes at withstanding slow and fast-changing stimulus and recordings. In this work, we present \textit{HermEIS}, a novel approach that leverages single cycle in-phase and quadrature signal integrations for reducing the massive data throughput characteristic of such high density acquisition systems. As an initial proof-of-concept, we demonstrate over 66 decades of impedance bandwidth (5×1025×104 Hz5\times10^{-2} - 5\times10^{4}\text{ Hz}) in a parallel 44-channel potentiostatic setup composed of a custom PCB with off-the-shelf electronics working in tandem with an FPGA.

Keywords

Cite

@article{arxiv.2403.07758,
  title  = {HermEIS: A Parallel Multichannel Approach to Rapid Spectral Characterization of Neural MEAs},
  author = {Akwasi Akwaboah and Ralph Etienne-Cummings},
  journal= {arXiv preprint arXiv:2403.07758},
  year   = {2024}
}

Comments

5 pages, submitted to IEEE EMBC 2024