A hybrid pre-processor for sleep staging using the E.E.G

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  • A detailed survey concerning the analysis of normal human sleep by examination of electroencephalogram (EEG) data is presented. A critical review of methods which have been undertaken towards automating this process is included to justify the use of a hybrid system for high speed (1/60 real time) automated sleep analysis. Two varieties of feature detectors which form the basis of a hybrid system are then discussed in detail. The application of monolithic phase-locked loops for detection of two specific components of normal sleep (the alpha rhythm and sigma spindles) is described and a detector (delta rhythm) based on zero-crossing, amplitude measurement principles is also investigated. The accuracy of each of the three feature detectors is presented and their potential as elements of a hybrid sleep analysis system is illustrated by the analysis of two all-night EEG recordings. Finally, recommendations for the continuing development of the system are suggested.

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  • Copyright © 1975 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

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  • 1975

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