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Updated: Jul 16, 2026
Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
Published on: June 5, 2019
Analysis of heart rate variability to predict patient age in a healthy population
V D A Corino1, M Matteucci, L T Mainardi
1Department of Biomedical Engineering, Politecnico di Milano, Via Golgi 39, 20133 Milano, Italy. valentina.corino@polimi.it
Objectives:
To estimate age of healthy subjects by means of the heart rate variability (HRV) parameters thus assessing the potentiality of HRV indexes as a biomarker of age.
Methods:
Long-term indexes of HRV in time domain, frequency domain and non-linear parameters were computed on 24-hour recordings in a dataset of 63 healthy subjects (age range 20-76 years old). Then, as interbeat dynamics markedly change with age, showing a reduced HRV in older subjects, we tried to capture age-related influence on HRV by principal component analysis and to predict the subject age by means of a feedforward neural network.
Results:
The network provides good prediction of patient age, even if a slight overestimation in the younger subjects and a slight underestimation in the older ones were observed. In addition, the important contribution of non-linear indexes to prediction is underlined.
Conclusions:
HRV as a predictor of age may lead to the definition of a new biomarker of aging.
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