» Articles » PMID: 30956880

Wearable EEG and Beyond

Overview
Journal Biomed Eng Lett
Date 2019 Apr 9
PMID 30956880
Citations 65
Authors
Affiliations
Soon will be listed here.
Abstract

The electroencephalogram (EEG) is a widely used non-invasive method for monitoring the brain. It is based upon placing conductive electrodes on the scalp which measure the small electrical potentials that arise outside of the head due to neuronal action within the brain. Historically this has been a large and bulky technology, restricted to the monitoring of subjects in a lab or clinic while they are stationary. Over the last decade much research effort has been put into the creation of "wearable EEG" which overcomes these limitations and allows the long term non-invasive recording of brain signals while people are out of the lab and moving about. This paper reviews the recent progress in this field, with particular emphasis on the electrodes used to make connections to the head and the physical EEG hardware. The emergence of conformal "tattoo" type EEG electrodes is highlighted as a key next step for giving very small and socially discrete units. In addition, new recommendations for the performance validation of novel electrode technologies are given, with standards in this area seen as the current main bottleneck to the wider take up of wearable EEG. The paper concludes by considering the next steps in the creation of next generation wearable EEG units, showing that a wide range of research avenues are present.

Citing Articles

Movement Disorders and Smart Wrist Devices: A Comprehensive Study.

Caroppo A, Manni A, Rescio G, Carluccio A, Siciliano P, Leone A Sensors (Basel). 2025; 25(1.

PMID: 39797057 PMC: 11723440. DOI: 10.3390/s25010266.


Driver fatigue recognition using limited amount of individual electroencephalogram.

Seo P, Kim H, Kim K Biomed Eng Lett. 2025; 15(1):143-157.

PMID: 39781053 PMC: 11704104. DOI: 10.1007/s13534-024-00431-x.


Overview of Wearable Healthcare Devices for Clinical Decision Support in the Prehospital Setting.

Gathright R, Mejia I, Gonzalez J, Hernandez Torres S, Berard D, Snider E Sensors (Basel). 2025; 24(24.

PMID: 39771939 PMC: 11679471. DOI: 10.3390/s24248204.


Exploring the Utility of the Muse Headset for Capturing the N400: Dependability and Single-Trial Analysis.

Hayes H, Magne C Sensors (Basel). 2025; 24(24.

PMID: 39771698 PMC: 11679084. DOI: 10.3390/s24247961.


A Method for the Spatial Interpolation of EEG Signals Based on the Bidirectional Long Short-Term Memory Network.

Hu W, Ji B, Gao K Sensors (Basel). 2024; 24(16).

PMID: 39204910 PMC: 11359714. DOI: 10.3390/s24165215.


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.
Xu J, Mitra S, Van Hoof C, Yazicioglu R, Makinwa K . Active Electrodes for Wearable EEG Acquisition: Review and Electronics Design Methodology. IEEE Rev Biomed Eng. 2017; 10:187-198. DOI: 10.1109/RBME.2017.2656388. View

3.
Symeonidou E, Nordin A, Hairston W, Ferris D . Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion. Sensors (Basel). 2018; 18(4). PMC: 5948545. DOI: 10.3390/s18041073. View

4.
Kohli S, Casson A . Towards out-of-the-lab EEG in uncontrolled environments: Feasibility study of dry EEG recordings during exercise bike riding. Annu Int Conf IEEE Eng Med Biol Soc. 2016; 2015:1025-8. DOI: 10.1109/EMBC.2015.7318539. View

5.
Matthews R, McDonald N, Hervieux P, Turner P, Steindorf M . A wearable physiological sensor suite for unobtrusive monitoring of physiological and cognitive state. Annu Int Conf IEEE Eng Med Biol Soc. 2007; 2007:5276-81. DOI: 10.1109/IEMBS.2007.4353532. View