A Novel Dry Electrode for Brain-Computer Interface
A brain-computer interface is a device that uses signals recorded from the brain to directly control a computer. In the last few years, P300-based brain-computer interfaces (BCIs) have proven an effective and reliable means of communication for people with severe motor disabilities such as amyotrophic lateral sclerosis (ALS). Despite this fact, relatively few individuals have benefited from currently available BCI technology. Independent BCI use requires easily acquired, good-quality electroencephalographic (EEG) signals maintained over long periods in less-than-ideal electrical environments. Conventional, wet-sensor, electrodes require careful application. Faulty or inadequate preparation, noisy environments, or gel evaporation can result in poor signal quality. Poor signal quality produces poor user performance, system downtime, and user and caregiver frustration. This study demonstrates that a hybrid dry electrode sensor array (HESA) performs as well as traditional wet electrodes and may help propel BCI technology to a widely accepted alternative mode of communication.
KeywordsBrain-computer interface P300 event-related potential dry electrode amyotrophic lateral sclerosis
Unable to display preview. Download preview PDF.
- 2.Nijboer, F., Sellers, E.W., Mellinger, J., Jordan, M.A., Matuz, T., Furdea, A., Mochty, U., Krusienski, D.J., Vaughan, T.M., Wolpaw, J.R., Birbaumer, N., Kübler, A.: A brain-computer interface for people with amyotrophic lateral sclerosis. Clinical Neurophysiology 119(8), 1909–1916 (2008) PMID: 18571984CrossRefGoogle Scholar
- 5.Sellers, E.W., Vaughan, T.M., McFarland, D.J., Krusienski, D.J., Mackler, S.A., Cardillo, R.A., Schalk, G., Binder-Macleod, S.A., Wolpaw, J.R.: Daily use of a brain-computer interface by a man with ALS. In: Society for Neuroscience annual meeting, Atlanta, GA (2006)Google Scholar
- 6.Sellers, E.W., Vaughan, T.M., McFarland, D.J., Carmack, C.S., Schalk, G., Cardillo, R.A., Mackler, S.A., Braun, E.M., Halder, S., Lee, S., Fudrea, A., Kübler, A., Wolpaw, J.R.: Brain-Computer Interface for people with ALS: long-term daily use in the home environment. Program No. 414.5, Abstract Viewer/Itinerary Planner, Washington, DC. Society for Neuroscience (2007) (Online)Google Scholar
- 7.Sellers, E.W., Townsend, G., Boulay, C., LaPallo, B.K., Vaughan, T.M., Wolpaw, J.R.: The P300 brain-computer interface: A new stimulus presentation paradigm. Program No. 778.21, Abstract Viewer/Itinerary Planner, Washington, DC. Society for Neuroscience (2008) (Online)Google Scholar
- 10.Matthews, R., McDonald, N.J., Hervieux, P., Turner, P.J., Steindorf, M.A.: A Wearable Physiological Sensor Suite for Unobtrusive Monitoring of Physiological and Cognitive State, in Engineering in Medicine and Biology Society, 2007. In: EMBC 2007, Proceedings of the 29th Annual International Conference of the IEEE, August 22-26, 2007, vol. 26, pp. 5276–5281 (2007)Google Scholar
- 11.Matthews, R., Turner, P.J., McDonald, N.J., Ermolaev, K., McManus, T., Shelby, R.A., Steindorf, M.A.: Real Time Workload Classification from an Ambulatory Wireless EEG System Using Hybrid EEG Electrodes, presented during the Invited Session. In: Towards Truly Wearable Electroencephalography at the 30th Annual International IEEE EMBS Conference, Vancouver, British Columbia, Canada, August 20-24 (2008)Google Scholar
- 13.Donchin, E., Karis, D., Bashore, T.R., Coles, M.G.H., Gratton, G.: Cognitive psychophysiology and human information processing. In: Coles, M.G.H., Donchin, E., Porges, S.W. (eds.) Psychophysiology Systems, Processes and Applications, pp. 244–267. Guilford Press, New York (1986)Google Scholar
- 14.Fabiani, M., Gratton, G., Karis, D., Donchin, E.: Definition, identification, and reliability of measurement of the P300 component of the event-related brain potential. Advances in Psychophysiology 2, 1–78 (1987)Google Scholar