Number of classes from ECG and its application to ECG analysis.
- Author:
Jin QI
1
;
Zhiwen MO
Author Information
1. Institute of Mathematics, Sichuan Normal University, Chengdu 610066.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Databases, Factual;
Electrocardiography;
classification;
Humans
- From:
Journal of Biomedical Engineering
2002;19(2):225-228
- CountryChina
- Language:Chinese
-
Abstract:
The aim of this study was to detect QRS complex powers accurately. ECG was approximated by lines. It produced number of classes with main features of the whole ECG. Then these number of classes were analyzed in detail. The QRS detection rate reached 99.9% as validated by using single lead signals from MIT/BIH database. Complex powers can be recognized accurately with this method.
