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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3   p. 3627
Using Hidden Markov Models to Build an Automatic, Continuous and Probabilistic Sleep Stager
A. Flexer, The Austrian Research Institute for Artificial Intelligence
P. Sykacek, The Austrian Research Institute for Artificial Intelligence
G. Dorffner, The Austrian Research Institute for Artificial Intelligence
I. Rezek, University of Oxford

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861392
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Abstract
We report about an automatic continuous sleep stager, which is based on probabilistic principles employing Hidden Markov Models (HMM). Our sleep stager offers the advantage of being objective by not relying on human scorers, having much finer temporal resolution (1 second instead of 30 second), and being based on solid probabilistic principles rather than a predefined set of rules (Rechtschaffen & Kales). Results obtained for nine whole night sleep recordings are reported.
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Citation:  A. Flexer, P. Sykacek, G. Dorffner, I. Rezek, "Using Hidden Markov Models to Build an Automatic, Continuous and Probabilistic Sleep Stager," ijcnn, p. 3627,  IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3,  2000