Dry-Contact Electrode Ear-EEG

Objective: Ear-EEG is a recording method in which EEG signals are acquired from electrodes placed on an earpiece inserted into the ear. Thereby, ear-EEG provides a noninvasive and discreet way of recording EEG, and has the potential to be used for long-term brain monitoring in real-life environments. Whereas previously reported ear-EEG recordings have been performed with wet electrodes, the objective of this study was to develop and evaluate dry-contact electrode ear-EEG. Methods: To achieve a well-functioning dry-contact interface, a new ear-EEG platform was developed. The platform comprised actively shielded and nanostructured electrodes embedded in an individualized soft-earpiece. The platform was evaluated in a study of 12 subjects and four EEG paradigms: auditory steady-state response, steady-state visual evoked potential, mismatch negativity, and alpha-band modulation. Results: Recordings from the prototyped dry-contact ear-EEG platform were compared to conventional scalp EEG recordings. When all electrodes were referenced to a common scalp electrode (Cz), the performance was on par with scalp EEG measured close to the ear. With both the measuring electrode and the reference electrode located within the ear, statistically significant (p < 0.05) responses were measured for all paradigms, although for mismatch negativity, it was necessary to use a reference located in the opposite ear, to obtain a statistically significant response. Conclusion: The study demonstrated that dry-contact electrode ear-EEG is a feasible technology for EEG recording. Significance: The prototyped dry-contact ear-EEG platform represents an important technological advancement of the method in terms of user-friendliness, because it eliminates the need for gel in the electrode-skin interface.

[1]  S. Marzouk,et al.  Improved electrodeposited iridium oxide pH sensor fabricated on etched titanium substrates. , 2003, Analytical chemistry.

[2]  Jens Haueisen,et al.  Multichannel EEG with novel Ti/TiN dry electrodes , 2015 .

[3]  S. Debener,et al.  Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear , 2015, Scientific Reports.

[4]  Joong Hoon Lee,et al.  CNT/PDMS-based canal-typed ear electrodes for inconspicuous EEG recording , 2014, Journal of neural engineering.

[5]  Preben Kidmose,et al.  Study of impedance spectra for dry and wet EarEEG electrodes , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[6]  B. Conway,et al.  ESCA study of the state of iridium and oxygen in electrochemically and thermally formed iridium oxide films , 1984 .

[7]  O. Markand,et al.  Alpha Rhythms , 1990, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[8]  Thomas Lunner,et al.  Ear-EEG-Based Objective Hearing Threshold Estimation Evaluated on Normal Hearing Subjects , 2017, IEEE Transactions on Biomedical Engineering.

[9]  Jyh-Yeong Chang,et al.  Novel Dry Polymer Foam Electrodes for Long-Term EEG Measurement , 2011, IEEE Transactions on Biomedical Engineering.

[10]  Risto Näätänen,et al.  The Mismatch Negativity (MMN) , 2011 .

[11]  Qiang Li,et al.  A wearable ear-EEG recording system based on dry-contact active electrodes , 2016, 2016 IEEE Symposium on VLSI Circuits (VLSI-Circuits).

[12]  Preben Kidmose,et al.  A method for quantitative assessment of artifacts in EEG, and an empirical study of artifacts , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[13]  Preben Kidmose,et al.  A Study of Evoked Potentials From Ear-EEG , 2013, IEEE Transactions on Biomedical Engineering.

[14]  J Haueisen,et al.  Novel Multipin Electrode Cap System for Dry Electroencephalography , 2015, Brain Topography.

[15]  H. Jasper.  Report of the committee on methods of clinical examination in electroencephalography , 1958 .

[16]  James J. S. Norton,et al.  Soft, curved electrode systems capable of integration on the auricle as a persistent brain–computer interface , 2015, Proceedings of the National Academy of Sciences.

[17]  S. Cogan.  Neural stimulation and recording electrodes. , 2008, Annual review of biomedical engineering.

[18]  Esther Rodriguez-Villegas,et al.  Wearable Electroencephalography , 2010, IEEE Engineering in Medicine and Biology Magazine.

[19]  Kaare B. Mikkelsen,et al.  EEG Recorded from the Ear: Characterizing the Ear-EEG Method , 2015, Front. Neurosci..

[20]  Tzyy-Ping Jung,et al.  Dry-Contact and Noncontact Biopotential Electrodes: Methodological Review , 2010, IEEE Reviews in Biomedical Engineering.

[21]  R. Näätänen,et al.  The mismatch negativity (MMN): towards the optimal paradigm , 2004, Clinical Neurophysiology.

[22]  K. Rosenkranz,et al.  An in-the-ear platform for recording electroencephalogram , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[24]  S.F. Cogan,et al.  Electrodeposited iridium oxide for neural stimulation and recording electrodes , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[25]  Preben Kidmose,et al.  High-density ear-EEG , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[26]  José Higino Correia,et al.  New dry electrodes based on iridium oxide (IrO) for non-invasive biopotential recordings and stimulation , 2010 .

[27]  T. Jung,et al.  Dry and Noncontact EEG Sensors for Mobile Brain–Computer Interfaces , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[28]  Martin G Bleichner,et al.  Exploring miniaturized EEG electrodes for brain-computer interfaces. An EEG you do not see? , 2015, Physiological reports.

[29]  Preben Kidmose,et al.  Physiological artifacts in scalp EEG and ear-EEG , 2017, Biomedical engineering online.