DocumentCode :
1401132
Title :
Isomap Approach to EEG-Based Assessment of Neurophysiological Changes During Anesthesia
Author :
Kortelainen, Jukka ; Väyrynen, Eero ; Seppänen, Tapio
Author_Institution :
Dept. of Electr. & Inf. Eng., Univ. of Oulu, Oulu, Finland
Volume :
19
Issue :
2
fYear :
2011
fDate :
4/1/2011 12:00:00 AM
Firstpage :
113
Lastpage :
120
Abstract :
Increasing concentrations of anesthetics in the blood induce a continuum of neurophysiological changes, which reflect on the electroencephalogram (EEG). EEG-based depth of anesthesia assessment requires that the signal samples are correctly associated with the neurophysiological changes occurring at different anesthetic levels. A novel method is presented to estimate the phase of the continuum using the feature data extracted from EEG. The feature data calculated from EEG sequences corresponding to continuously deepening anesthesia are considered to form a one-dimensional nonlinear manifold in the multidimensional feature space. Utilizing a recently proposed algorithm, Isomap, the dimensionality of the feature data is reduced to achieve a one-dimensional embedding representing this manifold and thereby the continuum of neurophysiological changes during induction of anesthesia. The Isomap-based estimation is validated with data recorded from nine patients during induction of propofol anesthesia. The proposed method provides a novel approach to assess neurophysiological changes during anesthesia and offers potential for the development of more advanced systems for the depth of anesthesia monitoring.
Keywords :
biochemistry; blood; drugs; electroencephalography; neurophysiology; patient monitoring; spectral analysis; 1D nonlinear manifold; EEG-based assessment; Isomap approach; anesthesia depth monitoring; anesthetic level assessment; blood; electroencephalogram; multidimensional feature space; neurophysiological changes; propofol anesthesia; Anesthesia; Brain modeling; Classification algorithms; Electroencephalography; Estimation; Manifolds; Principal component analysis; Depth of anesthesia; dimensionality reduction; estimation; manifold learning; spectral analysis; Algorithms; Anesthesia; Anesthesia, Intravenous; Anesthetics; Anesthetics, Intravenous; Dose-Response Relationship, Drug; Electroencephalography; Humans; Monitoring, Intraoperative; Neurophysiology; Nonlinear Dynamics; Propofol; Reproducibility of Results; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2010.2098420
Filename :
5664799
Link To Document :
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