Probabilistic neural network approach for the detection of SAHS from overnight pulse oximetry.
Diagnosis of sleep apnea hypopnoea syndrome (SAHS) depends on the apnea-hypopnea index determined by the standard in-laboratory overnight polysomnography (PSG). PSG is a costly, labor intensive and, at times, inaccessible approach. Because of the high demand, the need for timely diagnosis and the as...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 51; no. 3; pp. 305 - 316 |
|---|---|
| Autores principales: | , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Mar2013
|
| 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=104243422&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104243422 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Mar2013 vid: 51 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104243422 NLM23160897 2012026355 10.1007/s11517-012-0995-4 NLM23160897 104243422 ppf: 305 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Probabilistic neural network approach for the detection of SAHS from overnight pulse oximetry. aug: au: Morillo, Daniel Sánchez Gross, Nicole affil: Biomedical Engineering and Telemedicine Lab, University of Cádiz, Cádiz, Spain, daniel.morillo@uca.es. sug: subj: Neural Networks (Computer) Oximetry Methods Polysomnography Methods Sleep Apnea, Obstructive Diagnosis Adult Aged Aged, 80 and Over Analysis of Variance Clinical Assessment Tools Female Human Male Middle Age Reproducibility of Results ROC Curve Sleep Apnea, Obstructive Physiopathology Adult: 19-44 years Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Female Male ab: Diagnosis of sleep apnea hypopnoea syndrome (SAHS) depends on the apnea-hypopnea index determined by the standard in-laboratory overnight polysomnography (PSG). PSG is a costly, labor intensive and, at times, inaccessible approach. Because of the high demand, the need for timely diagnosis and the associated costs, novel methods for SAHS detection are required. In this study, a novel multivariate system is proposed for SAHS detection from the analysis of overnight blood oxygen saturation (SpO2). 115 subjects with SAHS suspicion were studied. A starting set of 17 time domain, stochastic, frequency-domain and nonlinear features were initially computed from SpO2 recordings. Sequential forward feature selection and a probabilistic neural network with leave-one-out cross-validation were applied. Oxygen desaturations below a 4 % threshold within 30 s (ODI430), restorations of 4 % within 10 s (RES4), median value (Sat50), SD1 Poincaré descriptor and the relative power in the 0.013-0.067 Hz frequency band (PSD15/75) formed the optimum features subset. 92.4 % sensitivity and 95.9 % specificity were achieved. Results significantly outperformed the univariate and multivariate approaches reported in literature. The outcome is a simple cost-effective tool that could be used as an alternative or supplementary method in a domiciliary approach to early diagnosis of SAHS. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|