Real time workload classification from an ambulatory wireless EEG system using hybrid EEG electrodes

This paper describes a compact, lightweight and ultra-low power ambulatory wireless EEG system based upon QUASAR's innovative noninvasive bioelectric sensor technologies. The sensors operate through hair without skin preparation or conductive gels. Mechanical isolation built into the harness pe...

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Veröffentlicht in:2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2008-01, Vol.2008, p.5871-5875
Hauptverfasser: Matthews, R., Turner, P.J., McDonald, N. J., Ermolaev, K., Manus, T. Mc, Shelby, R.A., Steindorf, M.
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Sprache:eng
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Zusammenfassung:This paper describes a compact, lightweight and ultra-low power ambulatory wireless EEG system based upon QUASAR's innovative noninvasive bioelectric sensor technologies. The sensors operate through hair without skin preparation or conductive gels. Mechanical isolation built into the harness permits the recording of high quality EEG data during ambulation. Advanced algorithms developed for this system permit real time classification of workload during subject motion. Measurements made using the EEG system during ambulation are presented, including results for real time classification of subject workload.
ISSN:1094-687X
1557-170X
1558-4615
DOI:10.1109/IEMBS.2008.4650550