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Updated: Oct 1, 2026

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
Published on: June 5, 2019
Correlates of the shift in heart rate variability with an active postural change in a healthy population sample: The
Mercedes R Carnethon1, Duanping Liao, Gregory W Evans
1Stanford Center for Research in Disease Prevention, Stanford University School of Medicine, Palo Alto, CA, USA.
Background:
The heart rate variability (HRV) response to postural change is a sensitive measure of the shift in autonomic balance from parasympathetic to sympathetic predominance that, when attenuated or absent, has been correlated with prevalent disease in patient populations. In a healthy population sample, we evaluated whether the shift in HRV with postural change differed by demographic characteristics as well as whether it differed between participants with established coronary heart disease (CHD) risk factors and their counterparts.
Methods:
HRV was measured for 2 minutes in the supine and standing positions in a biracial sample of men and women (aged 45-64 years) without clinical CHD from the Atherosclerosis Risk In Communities Study (n = 7686). Mean differences among supine and standing mean R-R interval lengths, the SD of R-R intervals, and high-frequency power (HF) were compared by demographic characteristics (age, race, and sex) and CHD risk factors (smoking, obesity, physical activity, hypertension, and diabetes). Multivariable linear regression models were used to adjust for demographic characteristics.
Results:
Smaller changes in R-R intervals and larger changes in SD of R-R intervals with standing were found among participants who were obese, less physically active than their counterparts, hypertensive, and diabetic. Smaller changes in HF were identified in male and white participants, but there were no differences in HF by CHD risk factors once models were adjusted for demographic characteristics.
Conclusions:
These simple noninvasive measures can be used to detect differences in cardiac autonomic balance that may be markers for autonomic impairment in healthy adults.
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