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Objective: Daytime short nap involves individual physiological states including alertness and drowsiness. In order to have a better understanding of the periodical rhymes of physiological states and then promote a good interpretability of alertness, the aim of this study is to detect drowsiness during daytime short nap. Methods: A method of Bayesian-copula discriminant classifier (BCDC) was introduced...
In this study, the automatic technique for the continuous light sleep level estimation and prediction is developed. The ultimate purpose is to realize the automatic sleep level evaluation for short-term day time nap sleep. The main method is based on the conditional probability obtained according to the characteristics of neuro-physiological signals including EEG, EOG and EMG. The estimated and predicted...
In this paper, the vigilance levels during day time short nap sleep were estimated on the basis of Markov Process Amplitude (MPA) EEG model. The ultimate purpose was to adopt the MPA model to discriminate three levels of vigilance through a simple neural network. A set of parameters were firstly calculated based on MPA EEG model. Secondly, correlation analysis was adopted to extract effective parameters...
EEG is represented to referential derivation with ear lobe reference and bipolar derivations for quantitative interpretation. When the ear lobe was activated, referential derivation with ear lobe reference was contaminated by ear lobe artifacts. In this study, the focus and extension of EEG components were estimated based on the cross spectrum of bipolar derivation. A referential derivation was constructed...
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