loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Sergio A. Alvarez 1 and Carolina Ruiz 2

Affiliations: 1 Boston College, United States ; 2 Worcester Polytechnic Institute, United States

ISBN: 978-989-8565-36-5

Keyword(s): Time Series, Clustering, Modeling, Markov, Data Mining, Sleep.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics ; Sensor Networks ; Soft Computing

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 re sults obtained over a dataset of 875 human hypnograms are discussed. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 52.23.234.7

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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

@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},
}

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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.