Literature DB >> 31096191

A comparative evaluation of signal quality between a research-grade and a wireless dry-electrode mobile EEG system.

Francesco Marini1, Clement Lee, Johanna Wagner, Scott Makeig, Mateusz Gola.   

Abstract

OBJECTIVE: Electroencephalography (EEG) is widely used by clinicians, scientists, engineers and other professionals worldwide, with an increasing number of low-cost, commercially-oriented EEG systems that have become available in recent years. One such system is the Cognionics Quick-20 (Cognionics Inc., San Diego, USA), which uses dry electrodes and offers the convenience of portability thanks to its built-in amplifier and wireless connection. Because of such characteristics, this system has been used in several applications for both clinical and basic research studies. However, an investigation of the quality of the signals that are recorded using this system has not yet been reported. APPROACH: To bridge this gap, here we conducted a systematic comparison of signal quality between the Cognionics Quick-20 system and the Brain Products actiCAP/actiCHamp (Brain Products GmbH, Munich, Germany), a state-of-the-art, wet-electrode, research-oriented EEG system. Resting-state EEG data were recorded from twelve human participants at rest in eyes open and eyes closed conditions. For both systems we evaluated the similarity of mean recorded power spectral density, and detection of alpha suppression associated with eyes open relative to eyes closed. MAIN
RESULTS: Power spectral densities were highly correlated across systems, with only minor topographical variability across the scalp. Both systems recorded alpha suppression during eyes open relative to eyes closed conditions. SIGNIFICANCE: These results attest to the robustness and reliability of the dry-electrode Cognionics system relatively to the widely used Brain Products laboratory EEG system, and thus validate its utility for clinical and basic research purposes, at least in studies in which participants do not move.

Entities:  

Year:  2019        PMID: 31096191     DOI: 10.1088/1741-2552/ab21f2

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  8 in total

Review 1.  Progress in Brain Computer Interface: Challenges and Opportunities.

Authors:  Simanto Saha; Khondaker A Mamun; Khawza Ahmed; Raqibul Mostafa; Ganesh R Naik; Sam Darvishi; Ahsan H Khandoker; Mathias Baumert
Journal:  Front Syst Neurosci       Date:  2021-02-25

2.  Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion.

Authors:  Fareshte Erani; Nadezhda Zolotova; Benjamin Vanderschelden; Nima Khoshab; Hagop Sarian; Laila Nazarzai; Jennifer Wu; Bharath Chakravarthy; Wirachin Hoonpongsimanont; Wengui Yu; Babak Shahbaba; Ramesh Srinivasan; Steven C Cramer
Journal:  Stroke       Date:  2020-09-18       Impact factor: 7.914

3.  A newly developed free software tool set for averaging electroencephalogram implemented in the Perl programming language.

Authors:  Shugo Suwazono; Hiroshi Arao
Journal:  Heliyon       Date:  2020-11-26

4.  A CNN-Based Deep Learning Approach for SSVEP Detection Targeting Binaural Ear-EEG.

Authors:  Pasin Israsena; Setha Pan-Ngum
Journal:  Front Comput Neurosci       Date:  2022-05-19       Impact factor: 3.387

5.  Mobile Brain/Body Imaging of cognitive-motor impairment in multiple sclerosis: Deriving EEG-based neuro-markers during a dual-task walking study.

Authors:  Pierfilippo De Sanctis; Brenda R Malcolm; Peter C Mabie; Ana A Francisco; Wenzhu B Mowrey; Sonja Joshi; Sophie Molholm; John J Foxe
Journal:  Clin Neurophysiol       Date:  2020-02-21       Impact factor: 3.708

6.  A high-density 256-channel cap for dry electroencephalography.

Authors:  Patrique Fiedler; Carlos Fonseca; Eko Supriyanto; Frank Zanow; Jens Haueisen
Journal:  Hum Brain Mapp       Date:  2021-11-19       Impact factor: 5.038

7.  Large Vessel Occlusion Stroke Detection in the Prehospital Environment.

Authors:  Lauren Patrick; Wade Smith; Kevin J Keenan
Journal:  Curr Emerg Hosp Med Rep       Date:  2021-06-28

8.  An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States.

Authors:  Dalton J Edwards; Logan T Trujillo
Journal:  Brain Sci       Date:  2021-03-05
  8 in total

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