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helmet-based physiological signal monitoring system

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dc.contributor.authorKim, Youn Sung-
dc.contributor.authorBaek, Hyun Jae-
dc.contributor.authorKim, Jung Soo-
dc.contributor.authorLee, Haet Bit-
dc.contributor.authorChoi, Jong Min-
dc.contributor.authorPark, Kwang Suk-
dc.date.accessioned2009-03-16-
dc.date.available2009-03-16-
dc.date.issued2008-11-12-
dc.identifier.citationEuropean Journal of Applied Physiology 105(3):365-372en
dc.identifier.issn1439-6319-
dc.identifier.issn1439-6327-
dc.identifier.urihttps://hdl.handle.net/10371/1962-
dc.descriptionThis paper describes helmet-based wearable biosignal monitoring system that can measure ECG, EOG, EEG alpha wave and shows its application for detection of drowsiness.en
dc.descriptionauthors' final draft-
dc.description.abstractA helmet-based system that was able to monitor the drowsiness of a soldier was developed. The helmet system monitored the electrocardiogram, electrooculogram and electroencephalogram (alpha waves) without constraints. Six dry electrodes were mounted at five locations on the helmet: both temporal sides, forehead region and upper and lower jaw strips. The electrodes were connected to an amplifier that transferred signals to a laptop computer via Bluetooth wireless communication. The system was validated by comparing the signal quality with conventional recording methods. Data were acquired from three healthy male volunteers for 12 min twice a day whilst they were sitting in a chair wearing the sensor-installed helmet. Experimental results showed that physiological signals for the helmet user were measured with acceptable quality without any intrusions on physical activities. The helmet system discriminated between the alert and drowsiness states by detecting blinking and heart rate variability (HRV) parameters extracted from ECG. Blinking duration and eye reopening time were increased during the sleepiness state compared to the alert state. Also, positive peak values of the sleepiness state were much higher, and the negative peaks were much lower than that of the alert state. The LF/HF ratio also decreased during drowsiness. This study shows the feasibility for using this helmet system: the subjects health status and mental states could be monitored without constraints whilst they were working.en
dc.description.sponsorshipThis study was supported by a grant from the
Advanced Biometric Research Center (ABRC) and the Korea Science
and Engineering Foundation (KOSEF).
en
dc.language.isoen-
dc.publisherSpringer Verlagen
dc.relation.ispartofseries105en
dc.relation.ispartofseries3en
dc.subjecthelmeten
dc.subjectdry electrodesen
dc.subjectECGen
dc.subjectEOGen
dc.subjectEEGen
dc.subjectalpha waveen
dc.subjectdrowsinessen
dc.titlehelmet-based physiological signal monitoring systemen
dc.typeArticleen
dc.contributor.AlternativeAuthor김윤성-
dc.contributor.AlternativeAuthor백현재-
dc.contributor.AlternativeAuthor김정수-
dc.contributor.AlternativeAuthor이햇빛-
dc.contributor.AlternativeAuthor최종민-
dc.contributor.AlternativeAuthor박광석-
dc.identifier.doi10.1007/s00421-008-0912-6-
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Program in Bioengineering (협동과정-바이오엔지니어링전공)Journal Papers (저널논문_협동과정-바이오엔지니어링전공)
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