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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Vallverdu, M. Palacios, M. Hoyer, D. Claria, F. Baranowski, R. Caminal, P. |
| Copyright Year | 2004 |
| Description | Author affiliation: Dep. ESAII, Catalonia Tech. Univ., Barcelona, Spain (Vallverdu, M.; Palacios, M.) |
| Abstract | Synchronization and regularity between different rhythms were evaluated in the HRV using hidden Markov models (HMMs) at very low (VLF), low (LF) and high (HF) frequency bands. Phase synchronization of these rhythms was studied in RR series of hypertrophic cardiomyopathy (HCM) patients during the sleeping period. Two groups of patients were considered in the HCM group: high risk (HR), patients after aborted sudden death (SCD) or that died during follow up, and low risk (LR), patients without SCD. RR time-series were filtered in the following frequency-bands, VLF, LF and HF. The RR phase differences of HF vs. VLF, HF vs. LF and LF vs. VLF were calculated and then the amplitude range partitioned into 8 bins. Finally, these series (O, observations) were modeled using HMM. The models /spl lambda/ = (A,B,/spl pi/) were selected such that P(O//spl lambda/) was locally maximized. Ergodic topology and N = {5,10,15,20} states were considered also for this analysis. Ergodic HMMs with 10 states were found to be sufficient to characterize the HRV rhythms of HR and LR patients. Different synchronization strength was observed studying the phase entropies. However, only the parameters obtained from the HMM were able to differentiate the different groups, with p-value < 0.0005. |
| Starting Page | 600 |
| Ending Page | 603 |
| File Size | 245066 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780384393 |
| DOI | 10.1109/IEMBS.2004.1403229 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-09-01 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Rhythm Hidden Markov models Heart rate variability Cardiology Frequency synchronization Hafnium Heart rate Finite impulse response filter Time series analysis Electrocardiography phase synchronization Heart Rate Variability hidden Markov models |
| Content Type | Text |
| Resource Type | Article |
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