Key result
Low ECG sampling frequency (125 Hz) overestimates the HF index and underestimates the LF/HF index, with bias proportional to the inverse of the square sampling frequency.
ECG sampling frequency significantly impacts the accuracy of heart rate variability spectral indices, requiring caution when interpreting data from low-frequency recordings.
Caution advised for HRV spectral indices from low-frequency ECGs; leaves open minimum sampling standards for reliable clinical and research use.
Spectral analysis of the heart rate variability is becoming a usual tool as a marker of the autonomic nervous system. The final output of the spectral analysis is a set of indices that are always estimators due to technical limitations. In this work, the bias and the uncertainty in the VLF, LF, HF and LF/HF indices due to the finite sampling frequency of the ECG are analysed. The results indicate that for low sampling frequency (125 Hz), the bias and uncertainty in the HF and LF/HF indices can blur the results of the analysis, especially if the RR time series has low variability. The HF index is overestimated and, accordingly, the LF/HF index is underestimated. Then, results from RR time series with low sampling frequency must be used with care. The uncertainty of the spectral indices is proportional to the inverse of the sampling frequency and the bias is proportional to the inverse of the square sampling frequency.
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García-González et al. (2004) studied Heart rate variability spectral analysis. Low ECG sampling frequency was evaluated on Bias and uncertainty in VLF, LF, HF and LF/HF indices. Low ECG sampling frequency (125 Hz) overestimates the HF index and underestimates the LF/HF index, with bias proportional to the inverse of the square sampling frequency.
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