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Comparison of a Novel Dry Electrode Headset to Standard Routine EEG in Veterans

Halford, Jonathan J.; Schalkoff, Robert J.; Satterfield, Kevin E.; Martz, Gabriel U.; Kutluay, Ekrem; Waters, Chad G.; Dean, Brian C.

Journal of Clinical Neurophysiology: December 2016 - Volume 33 - Issue 6 - p 530–537
doi: 10.1097/WNP.0000000000000284
Original Research

Objective: This purpose of this study was to evaluate the usefulness of a prototype battery-powered dry electrode system (DES) EEG recording headset in Veteran patients by comparing it with standard EEG.

Methods: Twenty-one Veterans had both a standard electrode system recording and DES recording in nine different patient states at the same encounter. Setup time, patient comfort, and subject preference were measured. Three experts performed technical quality rating of each EEG recording in a blinded fashion using the web-based EEGnet system. Power spectra were compared between DES and standard electrode system recordings.

Results: The average time for DES setup was 5.7 minutes versus 21.1 minutes for standard electrode system. Subjects reported that the DES was more comfortable during setup. Most subjects (15 of 21) preferred the DES. On a five-point scale (1—best quality to 5—worst quality), the technical quality of the standard electrode system recordings was significantly better than for the DES recordings, at 1.25 versus 2.41 (P < 0.0001). But experts found that 87% of the DES EEG segments were of sufficient technical quality to be interpretable.

Conclusions: This DES offers quick and easy setup and is well tolerated by subjects. Although the technical quality of DES recordings was less than standard EEG, most of the DES recordings were rated as interpretable by experts.

Significance: This DES, if improved, could be useful for a telemedicine approach to outpatient routine EEG recording within the Veterans Administration or other health system.

*Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, U.S.A.;

Department of Neurology, Ralph H. Johnson Veterans Medical Center, Charleston, South Carolina, U.S.A.;

Department of Electrical and Computer Engineering, Clemson University, Clemson, South Carolina, U.S.A.; and

§School of Computing, Clemson University, Clemson, South Carolina, U.S.A.

Address correspondence and reprint requests to Jonathan J. Halford, MD, 96 Jonathan Lucas St, Suite 307 CSB, MSC606, Charleston, SC 29425, U.S.A.; e-mail:

The authors declare no conflicts of interest.

Presented as posters at the American Epilepsy Society Annual Meeting in Washington D.C., December 2013 and at the American Clinical Neurophysiology Society Annual Meeting, Atlanta, GA, February, 2014.

© 2016 by the American Clinical Neurophysiology Society