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Identifying the recurrence of sleep apnea using a harmonic hidden Markov model

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Hadj-Amar, Beniamino, Finkenstädt, Bärbel, Fiecas, Mark and Huckstepp, Robert T. R. (2021) Identifying the recurrence of sleep apnea using a harmonic hidden Markov model. The Annals of Applied Statistics, 15 (3). pp. 1171-1193. doi:10.1214/21-AOAS1455

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Official URL: https://doi.org/10.1108/TLDR-06-2021-001410.1214/2...

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Abstract

We propose to model time-varying periodic and oscillatory processes by means of a hidden Markov model where the states are defined through the spectral properties of a periodic regime. The number of states is unknown along with the relevant periodicities, the role and number of which may vary across states. We address this inference problem by a Bayesian nonparametric hidden Markov model assuming a sticky hierarchical Dirichlet process for the switching dynamics between different states while the periodicities characterizing each state are explored by means of a trans-dimensional Markov chain Monte Carlo sampling step. We develop the full Bayesian inference algorithm and illustrate the use of our proposed methodology for different simulation studies as well as an application related to respiratory research which focuses on the detection of apnea instances in human breathing traces.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
R Medicine > RC Internal medicine
Divisions: Faculty of Science > Life Sciences (2010- )
Faculty of Science > Statistics
SWORD Depositor: Library Publications Router
Library of Congress Subject Headings (LCSH): Sleep apnea syndromes, Sleep apnea syndromes -- Statistical methods , Markov processes -- Numerical solutions , Monte Carlo method , Bayesian statistical decision theory
Journal or Publication Title: The Annals of Applied Statistics
Publisher: Institute of Mathematical Statistics
ISSN: 1932-6157
Official Date: September 2021
Dates:
DateEvent
September 2021Published
Volume: 15
Number: 3
Page Range: pp. 1171-1193
DOI: 10.1214/21-AOAS1455
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/L016710/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
MC/PC/15070[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265

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