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Wearable System Based on Ultra-Thin Parylene C Tattoo Electrodes for EEG Recording

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2023 Jan 21
PMID 36679563
Authors
Affiliations
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Abstract

In an increasingly interconnected world, where electronic devices permeate every aspect of our lives, wearable systems aimed at monitoring physiological signals are rapidly taking over the sport and fitness domain, as well as biomedical fields such as rehabilitation and prosthetics. With the intent of providing a novel approach to the field, in this paper we discuss the development of a wearable system for the acquisition of EEG signals based on a portable, low-power custom PCB specifically designed to be used in combination with non-conventional ultra-conformable and imperceptible Parylene-C tattoo electrodes. The proposed system has been tested in a standard rest-state experiment, and its performance in terms of discrimination of two different states has been compared to that of a commercial wearable device for EEG signal acquisition (i.e., the Muse headset), showing comparable results. This first preliminary validation demonstrates the possibility of conveniently employing ultra-conformable tattoo-electrodes integrated portable systems for the unobtrusive acquisition of brain activity.

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References
1.
Norton J, Lee D, Lee J, Lee W, Kwon O, Won P . Soft, curved electrode systems capable of integration on the auricle as a persistent brain-computer interface. Proc Natl Acad Sci U S A. 2015; 112(13):3920-5. PMC: 4386388. DOI: 10.1073/pnas.1424875112. View

2.
Kim D, Lu N, Ma R, Kim Y, Kim R, Wang S . Epidermal electronics. Science. 2011; 333(6044):838-43. DOI: 10.1126/science.1206157. View

3.
Li G, Wang S, Li M, Duan Y . Towards real-life EEG applications: novel superporous hydrogel-based semi-dry EEG electrodes enabling automatically 'charge-discharge' electrolyte. J Neural Eng. 2021; 18(4). DOI: 10.1088/1741-2552/abeeab. View

4.
Katsigiannis S, Ramzan N . DREAMER: A Database for Emotion Recognition Through EEG and ECG Signals From Wireless Low-cost Off-the-Shelf Devices. IEEE J Biomed Health Inform. 2017; 22(1):98-107. DOI: 10.1109/JBHI.2017.2688239. View

5.
Baltatzis V, Bintsi K, Apostolidis G, Hadjileontiadis L . Bullying incidences identification within an immersive environment using HD EEG-based analysis: A Swarm Decomposition and Deep Learning approach. Sci Rep. 2017; 7(1):17292. PMC: 5725430. DOI: 10.1038/s41598-017-17562-0. View