Fast detrending of unevenly sampled series with application to HRV

Detrending RR series is a common processing step prior to HRV analysis. In the classical approaches RR series, which are inherently unevenly sampled, are interpolated and uniformly resampled, thus introducing errors in subsequent HRV analysis. In this paper, we propose a novel approach to detrending...

Full description

Saved in:
Bibliographic Details
Published inComputing in Cardiology 2013 pp. 417 - 420
Main Authors Villani, Valeria, Fasano, Antonio
Format Conference Proceeding
LanguageEnglish
Published n/a 01.09.2013
Subjects
Algorithm design and analysis
Frequency-domain analysis
Heart rate variability
MATLAB
Simulation
Vectors
Online AccessGet full text
ISBN1479908843
9781479908844
ISSN0276-6574

Cover

More Information
Summary:Detrending RR series is a common processing step prior to HRV analysis. In the classical approaches RR series, which are inherently unevenly sampled, are interpolated and uniformly resampled, thus introducing errors in subsequent HRV analysis. In this paper, we propose a novel approach to detrending unevenly sampled series and apply it to RR series. The approach is based on the notion of weighted quadratic variation, which is a suitable measure of variability for unevenly sampled series. Detrending is performed by solving a constrained convex optimization problem that exploits the weighted quadratic variation. Numerical results confirm the effectiveness of the approach. The algorithm is simple and 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.
ISBN:1479908843
9781479908844
ISSN:0276-6574