Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 4 August 2023 / Approved: 7 August 2023 / Online: 8 August 2023 (14:38:10 CEST)

A peer-reviewed article of this Preprint also exists.

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, 7440. 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, 7440.

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 are included 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 hours 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.

Keywords

Electroencephalogram (EEG); Mobile EEG, Bluetooth; Resting State; Eyes Open/Closed

Subject

Engineering, Bioengineering

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