دورية أكاديمية
Long-term heart rate variability as a predictor of patient age.
| العنوان: | Long-term heart rate variability as a predictor of patient age. |
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| المؤلفون: | Corino VD; Department of Biomedical Engineering, Polytechnic University of Milan, Milan, Italy. valentina.corino@polimi.it, Matteucci M, Cravello L, Ferrari E, Ferrari AA, Mainardi LT |
| المصدر: | Computer methods and programs in biomedicine [Comput Methods Programs Biomed] 2006 Jun; Vol. 82 (3), pp. 248-57. Date of Electronic Publication: 2006 May 26. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Scientific Publishers Country of Publication: Ireland NLM ID: 8506513 Publication Model: Print-Electronic Cited Medium: Print ISSN: 0169-2607 (Print) Linking ISSN: 01692607 NLM ISO Abbreviation: Comput Methods Programs Biomed Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Limerick : Elsevier Scientific Publishers Original Publication: Amsterdam : Elsevier Science Publishers, c1984- |
| مواضيع طبية MeSH: | Aging* , Heart Rate*, Adult ; Aged ; Aged, 80 and over ; Electrocardiography ; Female ; Humans ; Linear Models ; Male ; Middle Aged ; Models, Cardiovascular ; Neural Networks, Computer ; Nonlinear Dynamics ; Principal Component Analysis |
| مستخلص: | Patients age has been estimated in healthy population by means of the heart rate variability (HRV) parameters to assess the potentiality of HRV indexes as a biomarker of age. A long-term analysis of HRV has been performed, computing linear time and frequency domain parameters as well as non-linear metrics, in a dataset of 113 healthy subjects (age range 20-85 years old). The principal component analysis has been used to capture age-related influence on HRV and then three different models have been applied to predict subjects age: a robust linear regressor (RLR), a feedforward neural network (FFNN) and a radial basis function neural network (RBFNN). A good prediction of patient age has been obtained (using all principal components, the Pearson correlation coefficient between predicted and real age: RLR=0.793; FFNN=0.872; RBFNN=0.829), even if an overestimation in younger subjects and an underestimation in older ones may be observed. The important and complementary contribution of non-linear indexes to aging related HRV modifications has also been underlined. |
| تواريخ الأحداث: | Date Created: 20060530 Date Completed: 20061025 Latest Revision: 20191210 |
| رمز التحديث: | 20221213 |
| DOI: | 10.1016/j.cmpb.2006.04.005 |
| PMID: | 16730388 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 0169-2607 |
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| DOI: | 10.1016/j.cmpb.2006.04.005 |