Multivariate short-term heart rate variability: a pre-diagnostic tool for screening heart disease.
This study has aimed to develop a novel pre-diagnostic tool for primary care screening of heart disease based on multivariate short-term heart rate variability (HRV) analyzed by linear (time and frequency domain) and nonlinear methods (compression entropy (CE), detrended fluctuation analysis (DFA),...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 49; no. 1; pp. 41 - 51 |
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| Autores principales: | , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Jan2011
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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=104569762&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104569762 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jan2011 vid: 49 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104569762 NLM21140234 2010918996 10.1007/s11517-010-0719-6 NLM21140234 104569762 ppf: 41 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Multivariate short-term heart rate variability: a pre-diagnostic tool for screening heart disease. aug: au: Heitmann A Huebner T Schroeder R Perz S Voss A Heitmann, Andreas Huebner, Thomas Schroeder, Rico Perz, Siegfried Voss, Andreas affil: Department of Medical Engineering and Biotechnology, University of Applied Sciences Jena, Jena, Germany sug: subj: Heart Diseases Diagnosis Heart Rate Physiology Health Screening Methods Adult Aged Electrocardiography Methods Female Male Middle Age Primary Health Care Methods Signal Processing, Computer Assisted Young Adult Adult: 19-44 years Aged: 65+ years Middle Aged: 45-64 years Female Male ab: This study has aimed to develop a novel pre-diagnostic tool for primary care screening of heart disease based on multivariate short-term heart rate variability (HRV) analyzed by linear (time and frequency domain) and nonlinear methods (compression entropy (CE), detrended fluctuation analysis (DFA), Poincaré plot analysis, symbolic dynamics) applied to 5-min ECG segments. Firstly, we applied HRV analysis to separate healthy subjects (REF) from heart disease patients (PAT). Then to optimize the results, we subdivided both groups according to gender: REF (♂ = 78, ♀ = 53) versus PAT (♂ = 378, ♀ = 115). Finally, we divided REF and PAT into two age subgroups (30-50 years vs. 51-70 years of age) to consider the influence of age on HRV. Heart disease patients were classified using a scoring system based on cut-off values calculated from all HRV indices obtained from the REF. After combining the optimum indices from all different analyzing methods, sensitivities of more than 72% and a specificity of 100% in all subgroups were revealed. Nonlinear indices proved to be better for discriminating heart disease patients from healthy subjects. Multivariate short-term HRV, analyzed by both linear and nonlinear methods appears to be a suitable pre-diagnostic tool for screening heart disease in primary care settings. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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