Collective Probabilistic Dynamical Modeling of Sleep Stage Transitions

Sergio A. Alvarez, Carolina Ruiz

Abstract

This paper presents a new algorithm for time series dynamical modeling using probabilistic state-transition models, including Markov and semi-Markov chains and their variants with hidden states (HMM and HSMM). This algorithm is evaluated over a mixture of Markov sources, and is applied to the study of human sleep stage dynamics. The proposed technique iteratively groups data instances by dynamical similarity, while simultaneously inducing a state-transition model for each group. This simultaneous clustering and modeling approach reduces model variance by selectively pooling the data available for model induction according to dynamical characteristics. Our algorithm is thus well suited for applications such as sleep stage dynamics in which the number of transition events within each individual data instance is very small. The use of semi-Markov models within the proposed algorithm allows capturing non-exponential state durations that are observed in certain sleep stages. Preliminary results obtained over a dataset of 875 human hypnograms are discussed.

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Paper Citation


in Harvard Style

A. Alvarez S. and Ruiz C. (2013). Collective Probabilistic Dynamical Modeling of Sleep Stage Transitions . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 209-214. DOI: 10.5220/0004243102090214


in Bibtex Style

@conference{biosignals13,
author={Sergio A. Alvarez and Carolina Ruiz},
title={Collective Probabilistic Dynamical Modeling of Sleep Stage Transitions},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},
year={2013},
pages={209-214},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004243102090214},
isbn={978-989-8565-36-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - Collective Probabilistic Dynamical Modeling of Sleep Stage Transitions
SN - 978-989-8565-36-5
AU - A. Alvarez S.
AU - Ruiz C.
PY - 2013
SP - 209
EP - 214
DO - 10.5220/0004243102090214