Computational Modeling of Sleep Stage Dynamics using Weibull Semi-Markov Chains

Chiying Wang, Sergio A. Alvarez, Carolina Ruiz, Majaz Moonis

Abstract

In this paper, a semi-Markov chain of sleep stages is considered as a model of human sleep dynamics. Both sleep stage transitions and the durations of continuous bouts in each stage are taken into account. The semi-Markov chain comprises an underlying Markov chain that models the temporal sequence of sleep stages but not the timing details, together with a separate statistical model of the bout durations in each stage. The stage bout durations are modeled explicitly, by the Weibull parametric family of probability distributions. This family is found to provide good fits for the durations of waking bouts and of bouts in the NREM and REM sleep stages. A collection of 244 all-night hypnograms is used for parameter optimization of the Weibull bout duration distributions for specific stages. The Weibull semi-Markov chain model proposed in this paper improves considerably on standard Markov chain models, which force geometrically distributed (discrete exponential) stage bout durations for all stages, contradicting known experimental observations. Our results provide more realistic dynamical modeling of sleep stage dynamics that can be expected to facilitate the discovery of interesting and useful dynamical patterns in human sleep data in future work.

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Paper Citation


in Harvard Style

Wang C., A. Alvarez S., Ruiz C. and Moonis M. (2013). Computational Modeling of Sleep Stage Dynamics using Weibull Semi-Markov Chains . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013) ISBN 978-989-8565-37-2, pages 122-130. DOI: 10.5220/0004252801220130


in Bibtex Style

@conference{healthinf13,
author={Chiying Wang and Sergio A. Alvarez and Carolina Ruiz and Majaz Moonis},
title={Computational Modeling of Sleep Stage Dynamics using Weibull Semi-Markov Chains},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013)},
year={2013},
pages={122-130},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004252801220130},
isbn={978-989-8565-37-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013)
TI - Computational Modeling of Sleep Stage Dynamics using Weibull Semi-Markov Chains
SN - 978-989-8565-37-2
AU - Wang C.
AU - A. Alvarez S.
AU - Ruiz C.
AU - Moonis M.
PY - 2013
SP - 122
EP - 130
DO - 10.5220/0004252801220130