Back to Search
Start Over
Design of Classifier for Electrocardiography Classification
- Source :
- IFMBE Proceedings ISBN: 9789811358586
- Publication Year :
- 2019
- Publisher :
- Springer Singapore, 2019.
-
Abstract
- The Electrocardiography classifier is an essential tool for helping doctors in diagnosing early heart problems. This paper proposes with an electrocardiography classifier for analyzing accuracy in case of non-long-tail effect. Data are obtained from MIT-BIH arrhythmia database. Therefore, a discrete wavelet transform decomposition algorithm is employed for feature extraction and a principal component analysis is used for dimension reduction of data. In addition, the heart beat can be classified using a neural network method. In order to evaluate the classifier accuracy, the confusion matrix and Receiver Operating Characteristic curve are applied.
- Subjects :
- Discrete wavelet transform
Artificial neural network
Receiver operating characteristic
Computer science
business.industry
Dimensionality reduction
Feature extraction
Confusion matrix
Pattern recognition
ComputingMethodologies_PATTERNRECOGNITION
Principal component analysis
Artificial intelligence
business
Classifier (UML)
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- IFMBE Proceedings ISBN: 9789811358586
- Accession number :
- edsair.doi...........844e9dd4b25000782d66a42dcdb83362