EEG entropy estimation using a Markov model of the EEG for sleep stage separation in human neonates

被引：0
|
作者：
Lofgren, Nils A. [1 ]
Outram, Nicholas [2 ]
Thordstein, Magnus [3 ]
机构：
[1] Univ Coll Boras, Sch Engn, Boras, Sweden
[2] Univ Plymouth, Sch Comp Commun & Elect, Plymouth PL4 8AA, Devon, England
[3] Sahlgrens Univ Hosp, Inst Neurosci & Physiol, Sect Neurosci & Rehabil, Gothenburg, Sweden
来源：
2007 3RD INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING, VOLS 1 AND 2 | 2007年
关键词：
D O I：
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中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Entropy calculated on EEG has been shown to be a useful indicator of effects from insufficient oxygen supply. In this paper, the estimation of entropy is based on transition matrices instead of probability density functions. It is shown that the separation of sleep stages thereby can be improved. This suggests that by including time information given by the transition matrix in entropy estimates of the EEG, classification can be improved.
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页码：638 / +
页数：2
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