Automatic Classification of Arrhythmic Beats Using Gaussian Processes

被引：3

作者：

Skolidis, G. ^{[1
]}

Clayton, R. H. ^{[1
]}

Sanguinetti, G. ^{[1
]}

机构：

[1] Univ Sheffield, Dept Comp Sci, Sheffield S1 4DP, S Yorkshire, England

来源：

COMPUTERS IN CARDIOLOGY 2008, VOLS 1 AND 2 | 2008年

关键词：

D O I：

10.1109/CIC.2008.4749193

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a novel approach to the automated discrimination of normal and ventricular arrhythmic beats. The method employs Gaussian Processes, a non-parametric Bayesian technique which is equivalent to a neural network with infinite hidden nodes. The method is shown to perform competitively with other approaches on the MIT-BIH Arrhythmia Database. Furthermore, its probabilistic nature allows to obtain confidence levels on the predictions, which can be very useful to practitioners.

引用

页码：921 / 924

页数：4

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