Evidence map›Paper›PMID 22878608›Full record

ArticleJournal of neural engineering2012

Signal distortion from microelectrodes in clinical EEG acquisition systems.

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

Abstract read
In one paragraph

Article in Journal of neural engineering, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Data · 2024
    Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. On the nature of seizure dynamics.Brain : a journal of neurology · 2014
    Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

William C StaceyDepartment of Neurology, University of Michigan, Ann Arbor, MI, USA. William.stacey@umich.edu
Spencer Kellis
Paras R Patel
Bradley Greger
Christopher R Butson

Funding

Modeling seizure precursors and antiepileptic brain stimulationK08NS069783 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI STACEY, WILLIAM CHARLES · 2011 to 2015
$886k
NINDS NIH HHS K08 NS069783NINDS NIH HHS K08NS069783
6 · The paper itself

Abstract

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.

Indexed as

Electric ImpedanceElectrodes, ImplantedElectroencephalographyHumansMicroelectrodes

Identifiers

PMID22878608
PMCPMC3476479

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.