Key result
Inaccuracy in R-R time series of ≥4 ms significantly altered the root mean square of successive standard deviations (rMSSD) during exercise.
Why the study?
The study aimed to quantify the effect of inaccuracy in R-R time series on heart rate variability indexes.
Does inaccuracy in R-R time series affect heart rate variability indexes in healthy subjects?
Does inaccuracy in R-R time series affect heart rate variability indexes in healthy subjects?
Answers are grounded in this paper and cite their sources.
Inaccuracy in R-R measurement significantly affects HRV indexes, particularly during exercise, highlighting the need for high measurement accuracy.
Our study aims to quantify the effect of inaccuracy in the R-R times series on heart rate variability (HRV) indexes. Starting from 75 series measured in supine, standing and submaximal exercise situations in 25 healthy male subjects, we generated 15 new R-R time series with accuracy from ±2 to 30 ms. HRV analyses was performed on the 1200 obtained series and compared with the results of the original series. The results showed that during supine, HRV indexes were moderately affected by inaccuracy up to ±30 ms. However, during standing, the indexes were affected to a greater degree and it was even more evident during exercise: in this later case significant difference in the root mean square of successive standard deviations (rMSSD), a commonly used parasympathetic index in sport sciences for both health and performance purposes, were observed when inaccuracy was equal or greater than 4 ms. Also, a relationship between inaccuracy and rMSSD was highlighted: the lower the rMSSD, the greater the error. Our study underscored the importance of the accuracy of R-R measurement for heart rate variability and provides recommendation regarding technology and measurement errors on final results.
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Cassirame et al. (2019) studied Healthy (n=25). Inaccuracy in R-R time series vs. Original accurate R-R time series was evaluated on Heart rate variability (HRV) indexes. Inaccuracy in R-R time series of ≥4 ms significantly altered the root mean square of successive standard deviations (rMSSD) during exercise.
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