{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/hermeis-a-parallel-multichannel-approach-to","title":"HermEIS: A Parallel Multichannel Approach to Rapid Spectral Characterization of Neural MEAs","arxiv_id":"2403.07758","date":"2024-03-12","proceeding":null,"authors":["Akwasi Akwaboah","Ralph Etienne-Cummings"],"abstract":"The promise of increasing channel counts in high density ($> 10^4$) 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. $Z_{1 \\text{kHz}}$). 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 $6$ decades of impedance bandwidth ($5\\times10^{-2} - 5\\times10^{4}\\text{ Hz}$) in a parallel $4$-channel potentiostatic setup composed of a custom PCB with off-the-shelf electronics working in tandem with an FPGA.","url_abs":"https://arxiv.org/abs/2403.07758v1","url_pdf":"https://arxiv.org/pdf/2403.07758v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"hermeis-a-parallel-multichannel-approach-to","repo_url":"https://github.com/adakwaboah/hermeis_iq","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[{"method_slug":"pcb","method_name":"PCB"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}