Key result
Artificial noise added to beat-to-beat intervals revealed that commonly used HRV parameters like pNN50 and LF/HF ratio are highly sensitive to noise and show systematic biases.
Why the study?
Beat detection in ECGs can yield erroneous interval data, which may result in misleading heart rate variability parameter values and incorrect conclusions.
Answers are grounded in this paper and cite their sources.
Researchers should interpret HRV parameters like pNN50 and LF/HF ratio with caution due to their high sensitivity to beat-to-beat interval noise and resulting systematic biases.
Heart rate variability (HRV) analysis is often used to estimate human health and fitness status. More specifically, a range of parameters that express the variability in beat-to-beat intervals are calculated from electrocardiogram beat detections. Since beat detection may yield erroneous interval data, these errors travel through the processing chain and may result in misleading parameter values that can lead to incorrect conclusions. In this study, we utilized Monte Carlo simulation on real data, Kolmogorov-Smirnov tests and Bland-Altman analysis to carry out extensive analysis of the noise sensitivity of different HRV parameters. The used noise models consider Gaussian and student-t distributed noise. As a result we observed that commonly used HRV parameters (e.g. pNN50 and LF/HF ratio) are especially sensitive to noise and that all parameters show biases to some extent. We conclude that researchers should be careful when reporting different HRV parameters, consider the distributions in addition to mean values, and consider reference data if applicable. The analysis of HRV parameter sensitivity to noise and resulting biases presented in this work generalizes over a wide population and can serve as a reference and thus provide a basis for the decision about which HRV parameters to choose under similar conditions.
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Rohr et al. (2024) studied Healthy volunteers (n=971). Artificial noise in beat-to-beat intervals vs. Ground truth (no added noise) was evaluated on Sensitivity of HRV parameters to noise (bias, MAE, RMSE). Artificial noise added to beat-to-beat intervals revealed that commonly used HRV parameters like pNN50 and LF/HF ratio are highly sensitive to noise and show systematic biases.
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