Abstract：
:Distinguishing between awake and anesthetized states is one of the important problems in surgery. Vital signals contain valuable information that can be used in prediction of different levels of anesthesia. Some monitors based on electroencephalogram (EEG) such as the Bispectral (BIS) index have been proposed in recent years. This study proposes a new method for characterizing between awake and anesthetized states. We validated our method by obtaining data from 25 patients during the cardiac surgery that requires cardiopulmonary bypass. At first, some linear and non-linear features are extracted from EEG signals. Then a method called "LLE"(Locally Linear Embedding) is used to map high-dimensional features in a three-dimensional output space. Finally, low dimensional data are used as an input to a quadratic discriminant analyzer (QDA). The experimental results indicate that an overall accuracy of 88.4 % can be obtained using this method for classifying the EEG signal into conscious and unconscious states for all patients. Considering the reliability of this method, we can develop a new EEG monitoring system that could assist the anesthesiologists to estimate the depth of anesthesia accurately.
journal_name
J Med Systjournal_title
Journal of medical systemsauthors
Mirsadeghi M,Behnam H,Shalbaf R,Jelveh Moghadam Hdoi
10.1007/s10916-015-0382-4subject
Has Abstractpub_date
2016-01-01 00:00:00pages
13issue
1eissn
0148-5598issn
1573-689Xpii
10.1007/s10916-015-0382-4journal_volume
40pub_type
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pub_type： 杂志文章
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更新日期：2017-03-01 00:00:00
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更新日期：1983-08-01 00:00:00
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更新日期：1998-08-01 00:00:00
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更新日期：2011-06-01 00:00:00
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更新日期：2011-12-01 00:00:00
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