Use of Fourier analysis and discriminant function analysis of electroencephalogram to determine anesthetic depth

Persistent Link:
http://hdl.handle.net/10150/276613
Title:
Use of Fourier analysis and discriminant function analysis of electroencephalogram to determine anesthetic depth
Author:
Rose, Debra Schafer, 1958-
Issue Date:
1987
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
This study uses statistical techniques to determine anesthetic depths of three females undergoing total abdominal hysterectomies. Spectral analysis of the electronencephalogram is employed to define changes in brain wave activity under different levels of anesthesia after administration of diazepam and isoflurane. The multivariate statistical technique of discriminant function analysis is used to determine which frequencies, or linear combinations of frequencies, yield the most information for classification of the electronencephalogram samples into one of the three anesthetic depths (mild sedation, moderate anesthesia, and anesthetic sleep). Spectral analysis of the electronencephalogram showed similar results for all three patients after administration of diazepam (mild sedation), but widely varying results among patients during anesthesia using isoflurane. The combination of spectral analysis and discriminant function analysis showed reliable discrimination among the three anesthetic depths. The ability to discriminate was significantly improved when only two anesthetic depths were used.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Electroencephalography -- Analysis.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College; Electrical and Computer Engineering
Degree Grantor:
University of Arizona
Advisor:
Mylrea, Kenneth C.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleUse of Fourier analysis and discriminant function analysis of electroencephalogram to determine anesthetic depthen_US
dc.creatorRose, Debra Schafer, 1958-en_US
dc.contributor.authorRose, Debra Schafer, 1958-en_US
dc.date.issued1987en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThis study uses statistical techniques to determine anesthetic depths of three females undergoing total abdominal hysterectomies. Spectral analysis of the electronencephalogram is employed to define changes in brain wave activity under different levels of anesthesia after administration of diazepam and isoflurane. The multivariate statistical technique of discriminant function analysis is used to determine which frequencies, or linear combinations of frequencies, yield the most information for classification of the electronencephalogram samples into one of the three anesthetic depths (mild sedation, moderate anesthesia, and anesthetic sleep). Spectral analysis of the electronencephalogram showed similar results for all three patients after administration of diazepam (mild sedation), but widely varying results among patients during anesthesia using isoflurane. The combination of spectral analysis and discriminant function analysis showed reliable discrimination among the three anesthetic depths. The ability to discriminate was significantly improved when only two anesthetic depths were used.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectElectroencephalography -- Analysis.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorMylrea, Kenneth C.en_US
dc.identifier.proquest1332482en_US
dc.identifier.oclc19453329en_US
dc.identifier.bibrecord.b16774383en_US
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