Evidence map›Paper›PMID 30893791›Full record

ArticleSensors (Basel, Switzerland)2019

The Dry Revolution: Evaluation of Three Different EEG Dry Electrode Types in Terms of Signal Spectral Features, Mental States Classification and Usability.

Gianluca Di Flumeri, Pietro Aricò, Gianluca Borghini, Nicolina Sciaraffa, Antonello Di Florio, Fabio Babiloni

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.

0numbers the graph read from it
0cells of the map it votes in
65citing 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

65 citing papers in PubMed.

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  13. Wireless ear EEG to monitor drowsiness.Nature communications · 2024
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5 more citing papers are in PubMed but not listed here.

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

6 authors.

Gianluca Di FlumeriDepartment of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy. gianluca.diflumeri@uniroma1.it.ORCID 0000-0003-4426-051X
Pietro AricòDepartment of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy. pietro.arico@uniroma1.it.ORCID 0000-0002-3831-6620
Gianluca BorghiniDepartment of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy. gianluca.borghini@uniroma1.it.ORCID 0000-0001-8560-5671
Nicolina SciaraffaBrainSigns srl, via Sesto Celere, 00152 Rome, Italy. nicolina.sciaraffa@brainsigns.com.
Antonello Di FlorioBrainSigns srl, via Sesto Celere, 00152 Rome, Italy. antonello.diflorio@brainsigns.com.
Fabio BabiloniDepartment of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy. fabio.babiloni@uniroma1.it.ORCID 0000-0002-4962-176X

Funding

European Commission 723386Ministero dell'Istruzione, dell'Università e della Ricerca BrainSafeDrive
6 · The paper itself

Abstract

One century after the first recording of human electroencephalographic (EEG) signals, EEG has become one of the most used neuroimaging techniques. The medical devices industry is now able to produce small and reliable EEG systems, enabling a wide variety of applications also with no-clinical aims, providing a powerful tool to neuroscientific research. However, these systems still suffer from a critical limitation, consisting in the use of wet electrodes, that are uncomfortable and require expertise to install and time from the user. In this context, dozens of different concepts of EEG dry electrodes have been recently developed, and there is the common opinion that they are reaching traditional wet electrodes quality standards. However, although many papers have tried to validate them in terms of signal quality and usability, a comprehensive comparison of different dry electrode types from multiple points of view is still missing. The present work proposes a comparison of three different dry electrode types, selected among the main solutions at present, against wet electrodes, taking into account several aspects, both in terms of signal quality and usability. In particular, the three types consisted in gold-coated single pin, multiple pins and solid-gel electrodes. The results confirmed the great standards achieved by dry electrode industry, since it was possible to obtain results comparable to wet electrodes in terms of signals spectra and mental states classification, but at the same time drastically reducing the time of montage and enhancing the comfort. In particular, multiple-pins and solid-gel electrodes overcome gold-coated single-pin-based ones in terms of comfort.

Indexed as

AdultArea Under CurveArtifactsBrainElectrodesElectroencephalographyGoldHumansMachine LearningMaleROC CurveSilverWearable Electronic DevicesGoldSilverbrain activitydry electrodeselectroencephalographyfrequency domainmachine-learningmental workloadpower spectral densitywearable deviceswet electrodes

Identifiers

PMID30893791
PMCPMC6470960

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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.