Authors:
David G. Márquez
1
;
Abraham Otero
2
;
Paulo Félix
1
and
Constantino A. García
1
Affiliations:
1
University of Santiago de Compostela, Spain
;
2
University San Pablo CEU, Spain
Keyword(s):
Heartbeat Representation, Hermite Functions, ECG.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Cardiovascular Signals
;
Computer Vision, Visualization and Computer Graphics
;
Detection and Identification
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
Automatic ECG analysis requires choosing a representation for heartbeats. A common approach is using some basis of functions to represent the heartbeat as a linear combination of these functions. The coefficients of the linear combination are used as the features that represent the heartbeat, providing a very compact representation. The most used basis of functions is the one made up of the Hermite functions. Some authors have used as few as 3 Hermite polynomials to represent each heartbeat, while others have used as many as 20. Often little or no justification for the choice of the number of polynomials is given. This paper aims to analyze the impact of using a certain number Hermite polynomials on the accuracy of heartbeat representation. Tests were run fitting the heartbeats of the MIT-BIH arrhythmia database with a number of polynomials ranging from 2 to 20. Three different strategies to determine the heartbeat’s position were used. The fitting errors are reported here. Based on
these results, some guidelines to choose a suitable number of Hermite polynomials for different applications are given.
(More)