NDLI: Comparing hidden Markov model and hidden semi-Markov model based detectors of apnea-bradycardia episodes in preterm infants

Content Provider	IEEE Xplore Digital Library
Author	Altuve, M. Carrault, G. Beuchee, A. Flamand, C. Pladys, P. Hernandez, A.I.
Copyright Year	2012
Description	Author affiliation: Inserm U1099, Rennes, F-35000, France (Carrault, G.; Beuchee, A.; Pladys, P.; Hernandez, A.I.) \|\| Grupo de Bioingeniería y Biofísica Aplicada, Universidad Simón Bolívar, Caracas, Venezuela (Altuve, M.) \|\| CHU Nantes, Service de réanimation pédiatrique, néonatologie et CIC, Nantes, France (Flamand, C.)
Abstract	In this paper, we propose, evaluate and compare two detectors of apnea-bradycardia episodes, based on hidden Markov models (HMM) and hidden semi-Markov models (HSMM). Evaluation is performed on a database of 233 apnea-bradycardia episodes manually annotated. The acquired ECG signals are processed to obtain RR series. The proposed detectors, applied to these RR series, are composed of two HMM or HSMM models, each one representing two distinct physiopathological states: absence and presence of apnea-bradycardia. A learning phase is firstly applied to each model in order to estimate their parameters from a learning dataset. Then, using a sliding window, the models are applied to a set of new observations, to compute the log-likelihood of each model for each time instant. Detection of the events of interest is based on the comparison of log-likelihoods with respect to a threshold. The optimal detection configuration was obtained in terms of sensitivity, specificity and detection delay. Results show that the analysis of the dynamics of RR series, through the HSMM, allows for a significant improvement of sensitivity (90.38% vs 88.42%) and specificity (92.23% vs 89.67%), with a reduction of the detection delay (0.92±3.56s vs 1.60±3.72s).
Starting Page	389
Ending Page	392
File Size	207304
Page Count	4
File Format	PDF
ISBN	9781467320764
ISSN	2325887X
e-ISBN	9781467320771
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-09
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Creative Commons Attribution License 2.5 (CCAL)
Subject Keyword	Hidden Markov models Detectors Delay Time series analysis Electrocardiography Quantization Sensitivity
Content Type	Text
Resource Type	Article
Subject	Computer Science Cardiology and Cardiovascular Medicine

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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