Fast Detrending of RR Series for HRV Analysis

Detrending RR series is a common processing step prior to HRV analysis. Classical approaches to detrending apply to uniformly sampled data. Thus, RR series, which are inherently unevenly sampled, are interpolated and uniformly resampled prior to detrending. However, this interpolation-resampling process introduces significant errors in the spectral analysis of HRV. We have recently proposed a novel approach to detrending unevenly sampled RR series, which is based on the notion of weighted quadratic variation reduction. In this paper, we assess its performance through statistical analysis. Numerical results confirm the effectiveness of the approach, which outperforms competing algorithms. Moreover, it allows easy implementation and is favorable in terms of computational complexity, which is linear in the size of the series to detrend. This makes it suitable for long-term HRV analysis. To the best of the authors’ knowledge, it is the fastest algorithm for detrending RR series.