Physiological Signal Processing in Heart Rate Variability Measurement: A Focus on Spectral Analysis

TL;DR

This paper discusses the use of FFT in HRV spectral analysis, highlighting issues with re-sampling uneven heartbeat data and its impact on measurement accuracy.

Contribution

It critically examines the limitations of FFT-based spectral analysis in HRV due to re-sampling errors in uneven heartbeat data.

Findings

Re-sampling introduces significant errors in HRV spectral estimates.

FFT requires evenly sampled data, which is problematic for RR tachograms.

Re-sampling can distort the true spectral content of HRV signals.

Abstract

Fast Fourier Transform (FFT) relies on the HRV frequency-domain analysis techniques. It requires re-sampling of the inherently unevenly sampled heartbeat time-series (RR tachogram) to produce an evenly sampled time series of the heartbeat. However, re-sampling of the heartbeat time -- series is found to produce a substantial error when estimating an artificial RR tachogram.