Paper
Classification of Myocardial Infraction Stages Using High-Frequency ECG
- Authors:
- Dingfei Ge
- Abstract
- Some existing researches reported that high frequency QRS complex (HF-QRS) is shown to be a more sensitive indicator of myocardial infarction (MI) and ischemia than that of standard ST segment analysis. It was investigated that HF-QRS was incorporated in the feature extraction to detect MI. An algorithm for different MI stage discrimination was proposed in this study, including clinical diagnosis parameter measurement from the derived steady electrocardiogram (ECG) patterns to represent a specific patient, feature extraction from HF-QRS, feature dimension reduction by linear discriminant analysis (LDA) and a relevance vector machine (RVM) based classification. The experimental results show that it is beneficial for MI classification using the features extracted from HF-QRS.
- Keywords
- High Frequency Electrocardiogram; Myocardial Iinfaraction; Feature Extraction; Relevance Vector Machine; Classification
- StartPage
- 77
- EndPage
- 80
- Doi