Combining hidden Markov models for comparing the dynamics of multiple sleep electroencephalograms.
Title | Combining hidden Markov models for comparing the dynamics of multiple sleep electroencephalograms. |
Publication Type | Journal Article |
Year of Publication | 2013 |
Authors | Langrock R, Swihart BJ, Caffo BS, Punjabi NM, Crainiceanu CM |
Journal | Stat Med |
Volume | 32 |
Issue | 19 |
Pagination | 3342-56 |
Date Published | 2013 Aug 30 |
ISSN | 1097-0258 |
Keywords | Data Interpretation, Statistical, Electroencephalography, Female, Humans, Longitudinal Studies, Male, Markov Chains, Middle Aged, Models, Statistical, Sleep Apnea Syndromes |
Abstract | In this manuscript, we consider methods for the analysis of populations of electroencephalogram signals during sleep for the study of sleep disorders using hidden Markov models (HMMs). Notably, we propose an easily implemented method for simultaneously modeling multiple time series that involve large amounts of data. We apply these methods to study sleep-disordered breathing (SDB) in the Sleep Heart Health Study (SHHS), a landmark study of SDB and cardiovascular consequences. We use the entire, longitudinally collected, SHHS cohort to develop HMM population parameters, which we then apply to obtain subject-specific Markovian predictions. From these predictions, we create several indices of interest, such as transition frequencies between latent states. Our HMM analysis of electroencephalogram signals uncovers interesting findings regarding differences in brain activity during sleep between those with and without SDB. These findings include stability of the percent time spent in HMM latent states across matched diseased and non-diseased groups and differences in the rate of transitioning. |
DOI | 10.1002/sim.5747 |
Alternate Journal | Stat Med |
PubMed ID | 23348835 |
PubMed Central ID | PMC3753805 |
Grant List | HL075078 / HL / NHLBI NIH HHS / United States R01 EB012547 / EB / NIBIB NIH HHS / United States R01 NS060910 / NS / NINDS NIH HHS / United States R01EB012547 / EB / NIBIB NIH HHS / United States R01NS060910 / NS / NINDS NIH HHS / United States |