Abstract
Methods for analyzing sleep should preserve the relevant information about the physiological sleep mechanism while removing the “noise”. Several probabilistic models of sleep and sleep-related signals (such as EEG, EOG, and EMG) differentiate the part of recorded signals that is noise from the part that reflects the relevant state (physiological, dynamical, pathological, etc.) of the system. The structure and parameters of such models can be based on statistical and physiological knowledge. Some models enable the design of algorithms for estimation or detection of the relevant signal characteristics while rejecting as much of the noise as possible.
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© 1991 Springer-Verlag Berlin Heidelberg
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Kemp, B., Kamphuisen, H.A.C. (1991). Model-Based Sleep Analysis. In: Peter, J.H., Penzel, T., Podszus, T., von Wichert, P. (eds) Sleep and Health Risk. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76034-1_6
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DOI: https://doi.org/10.1007/978-3-642-76034-1_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-53083-1
Online ISBN: 978-3-642-76034-1
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