Online apnea-bradycardia detection based on hidden semi-Markov models.
In this paper, we propose a new online apnea-bradycardia detection scheme that takes into account not only the instantaneous values of time series, but also their temporal evolution. The detector is based on a set of hidden semi-Markov models, representing the temporal evolution of beat-to-beat inte...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 53; no. 1; pp. 1 - 14 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Jan2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109773464&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109773464 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jan2015 vid: 53 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 109773464 NLM25300402 2012869312 10.1007/s11517-014-1207-1 NLM25300402 109773464 ppf: 1 ppct: 13 formats: fmt: @attributes: type: P tig: atl: Online apnea-bradycardia detection based on hidden semi-Markov models. aug: au: Altuve, Miguel Carrault, Guy Beuchée, Alain Pladys, Patrick Hernández, Alfredo I sug: subj: Apnea Diagnosis Bradycardia Diagnosis Probability Online Systems Apnea Ultrasonography Bradycardia Ultrasonography Electrocardiography Human Infant, Newborn Infant, Premature ROC Curve Sensitivity and Specificity Signal Processing, Computer Assisted Time Factors Infant, Newborn: birth-1 month ab: In this paper, we propose a new online apnea-bradycardia detection scheme that takes into account not only the instantaneous values of time series, but also their temporal evolution. The detector is based on a set of hidden semi-Markov models, representing the temporal evolution of beat-to-beat interval (RR interval) time series. A preprocessing step, including quantization and delayed version of the observation vector, is also proposed to maximize detection performance. This approach is quantitatively evaluated through simulated and real signals, the latter being acquired in neonatal intensive care units (NICU). Compared to two conventional detectors used in NICU, our best detector shows an improvement on average of around 15 % in sensitivity and 7 % in specificity. Furthermore, a reduced detection delay of approximately 2 s is also observed with respect to conventional detectors. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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