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Comparison of sleep-wake classification using electroencephalogram and wrist-worn multi-modal sensor data

Aug. 1, 2014

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Sano, Akane & Picard, Rosalind. (2014). Comparison of sleep-wake classification using electroencephalogram and wrist-worn multi-modal sensor data.

Abstract

This paper presents the comparison of sleep-wake classification using electroencephalogram (EEG) and multi-modal data from a wrist wearable sensor. We collected physiological data while participants were in bed: EEG, skin conductance (SC), skin temperature (ST), and acceleration (ACC) data, from 15 college students, computed the features and compared the intra-/inter-subject classification results. As results, EEG features showed 83% while features from a wrist wearable sensor showed 74% and the combination of ACC and ST played more important roles in sleep/wake classification.

via National Library of Medicine
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