Signal distortion from microelectrodes in clinical EEG acquisition systems

William C. Stacey, Spencer Kellis, Paras R. Patel, Bradley Greger, Christopher R. Butson

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Many centers are now using high-density microelectrodes during traditional intracranial electroencephalography (iEEG) both for research and clinical purposes. These microelectrodes are FDA-approved and integrate into clinical EEG acquisition systems. However, the electrical characteristics of these electrodes are poorly described and clinical systems were not designed to use them; thus, it is possible that this shift into clinical practice could have unintended consequences. In this study, we characterized the impedance of over 100 commercial macro- and microelectrodes using electrochemical impedance spectroscopy (EIS) to determine how electrode properties could affect signal acquisition and interpretation. The EIS data were combined with the published specifications of several commercial EEG systems to design digital filters that mimic the behavior of the electrodes and amplifiers. These filters were used to analyze simulated brain signals that contain a mixture of characteristic features commonly observed in iEEG. Each output was then processed with several common quantitative EEG measurements. Our results show that traditional macroelectrodes had low impedances and produced negligible distortion of the original signal. Brain tissue and electrical wiring also had negligible filtering effects. However, microelectrode impedances were much higher and more variable than the macroelectrodes. When connected to clinical amplifiers, higher impedance electrodes produced considerable distortion of the signal at low frequencies (<60 Hz), which caused significant changes in amplitude, phase, variance and spectral band power. In contrast, there were only minimal changes to the signal content for frequencies above 100 Hz. In order to minimize distortion with microelectrodes, we determined that an acquisition system should have an input impedance of at least 1 GΩ, which is much higher than most clinical systems. These results show that it is critical to account for variations in impedance when analyzing EEG from different-sized electrodes. Data from microelectrodes may yield misleading results unless recorded with high-impedance amplifiers.

Original languageEnglish (US)
Article number056007
JournalJournal of neural engineering
Issue number5
StatePublished - Oct 2012
Externally publishedYes

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience


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