Introducing a New Mobile Electroencephalography System and Evaluating Its Quality in Comparison to Clinical Electroencephalography

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https://doi.org/10.48693/515
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Title: Introducing a New Mobile Electroencephalography System and Evaluating Its Quality in Comparison to Clinical Electroencephalography
Authors: Samimisabet, Paria
Krieger, Laura
Nethar, Themis
Pipa, Gordon
ORCID of the author: https://orcid.org/0000-0002-3416-2652
Abstract: Electroencephalography (EEG) is a crucial tool in cognitive neuroscience, enabling the study of neurophysiological function by measuring the brain’s electrical activity. Its applications include perception, learning, memory, language, decision making and neural network mapping. Recently, interest has surged in extending EEG measurements to domestic environments. However, the high costs associated with traditional laboratory EEG systems have hindered accessibility for many individuals and researchers in education, research, and medicine. To tackle this, a mobile-EEG device named “DreamMachine” was developed. A more affordable alternative to both lab-based EEG systems and existing mobile-EEG devices. This system boasts 24 channels, 24-bit resolution, up to 6 h of battery life, portability, and a low price. Our open-source and open-hardware approach empowers cognitive neuroscience, especially in education, learning, and research, opening doors to more accessibility. This paper introduces the DreamMachine’s design and compares it with the lab-based EEG system “asalabTM” in an eyes-open and eyes-closed experiment. The Alpha band exhibited higher power in the power spectrum during eyes-closed conditions, whereas the eyes-open condition showed increased power specifically within the Delta frequency range. Our analysis confirms that the DreamMachine accurately records brain activity, meeting the necessary standards when compared to the asalabTM system.
Citations: Samimisabet P, Krieger L, Nethar T, Pipa G.: Introducing a New Mobile Electroencephalography System and Evaluating Its Quality in Comparison to Clinical Electroencephalography. Sensors. 2023; 23(17):7440
URL: https://doi.org/10.48693/515
https://osnadocs.ub.uni-osnabrueck.de/handle/ds-2024022810906
Subject Keywords: electroencephalogram (EEG); mobile EEG; Bluetooth; resting state; eyes open/closed
Issue Date: 26-Aug-2023
License name: Attribution 4.0 International
License url: http://creativecommons.org/licenses/by/4.0/
Type of publication: Einzelbeitrag in einer wissenschaftlichen Zeitschrift [Article]
Appears in Collections:FB08 - Hochschulschriften
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