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December 2013 Fréchet means of curves for signal averaging and application to ECG data analysis
Jérémie Bigot
Ann. Appl. Stat. 7(4): 2384-2401 (December 2013). DOI: 10.1214/13-AOAS676

Abstract

Signal averaging is the process that consists in computing a mean shape from a set of noisy signals. In the presence of geometric variability in time in the data, the usual Euclidean mean of the raw data yields a mean pattern that does not reflect the typical shape of the observed signals. In this setting, it is necessary to use alignment techniques for a precise synchronization of the signals, and then to average the aligned data to obtain a consistent mean shape. In this paper, we study the numerical performances of Fréchet means of curves which are extensions of the usual Euclidean mean to spaces endowed with non-Euclidean metrics. This yields a new algorithm for signal averaging and for the estimation of the time variability of a set of signals. We apply this approach to the analysis of heartbeats from ECG records.

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Jérémie Bigot. "Fréchet means of curves for signal averaging and application to ECG data analysis." Ann. Appl. Stat. 7 (4) 2384 - 2401, December 2013. https://doi.org/10.1214/13-AOAS676

Information

Published: December 2013
First available in Project Euclid: 23 December 2013

zbMATH: 54.0036.03
MathSciNet: MR3161727
Digital Object Identifier: 10.1214/13-AOAS676

Rights: Copyright © 2013 Institute of Mathematical Statistics

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Vol.7 • No. 4 • December 2013
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