Measurement of Signal-to-Noise Ratio in Neural Microelectrodes

Justin W. Stadlbauer, Sepideh Rastegar, David Estrada, Kurtis D. Cantley

Research output: Contribution to conferencePoster

Abstract

Signal noise has limited the performance and application of bioelectronics in areas such as neural interfaces and biosensors. Graphene, a two-dimensional hexagonal array of carbon atoms, shows promise as a material for bio-interface applications. This study explores the properties of graphene as a low-noise neural electrode material. Using glass-micropipette electrophysiology, signals are applied to solution-based microelectrode arrays and the response is precisely measured. Signal-to-noise ratio (SNR) is characterized and analyzed using concepts from signal theory on several material systems. These include indium-tin-oxide, various metals deposited by sputtering and inkjet printing, as well as large-area chemical vapor-deposited (CVD) graphene. Our hypothesis is that the unique chemical and electronic properties of graphene increases charge transfer and therefore lowers interfacial impedance at the biological/solid state interface. This effect is expected to be accompanied by increased SNR.

Original languageAmerican English
StatePublished - 1 Jul 2016
EventIdaho Conference on Undergraduate Research 2016 - Boise State University, Boise, United States
Duration: 1 Jul 2016 → …

Conference

ConferenceIdaho Conference on Undergraduate Research 2016
Abbreviated titleICUR 2016
Country/TerritoryUnited States
CityBoise
Period1/07/16 → …

EGS Disciplines

  • Electrical and Computer Engineering
  • Materials Science and Engineering

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