Biomed Eng Lett.  2017 Nov;7(4):325-332. 10.1007/s13534-017-0043-2.

ECG arrhythmia classification using time frequency distribution techniques

• Sultan Qurraie S
• Ghorbani Afkhami R

• KMID: 2397934
• DOI: http://doi.org/10.1007/s13534-017-0043-2

Abstract

In this paper, we focus on classifying cardiac arrhythmias. The MIT-BIH database is used with 14 original classes of labeling which is then mapped into 5 more general classes, using the Association for the Advancement of Medical Instrumentation standard. Three types of features were selected with a focus on the time-frequency aspects of ECG signal. After using the Wigner-Ville distribution the time-frequency plane is split into 9 windows considering the frequency bandwidth and time duration of ECG segments and peaks. The summation over these windows are employed as pseudo-energy features in classification. The "subject-oriented" scheme is used in classification, meaning the train and test sets include samples from different subjects. The subject-oriented method avoids the possible overfitting issues and guaranties the authenticity of the classification. The overall sensitivity and positive predictivity of classification is 99.67 and 98.92%, respectively, which shows a significant improvement over previous studies.

Keyword

Cardiac arrhythmia; Classification; Decision tree; Ensemble learner; Time-frequency analysis; Wigner-Ville distribution

MeSH Terms

Arrhythmias, Cardiac*
Classification*
Decision Trees
Electrocardiography*
Methods