Fr\'echet means of curves for signal averaging and application to ECG data analysis
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 Fr\'echet 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 without a reference template. We apply this approach to the estimation of a mean heart cycle from ECG records.
Keywords
Cite
@article{arxiv.1111.1855,
title = {Fr\'echet means of curves for signal averaging and application to ECG data analysis},
author = {Jérémie Bigot},
journal= {arXiv preprint arXiv:1111.1855},
year = {2011}
}