Characterization of ST-Segment using Wavelet transforms & Support vector machine
| Author(s) | : | Sunit Kumar, Maneesha Gupta, Amit Kumar Manocha |
| Institution | : | Department of Electronics & Communication Engineering, SKIET, Kurukshetra |
| Published In | : | Vol. 1, Issue 7 — July 2014 |
| Page No. | : | 13-22 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Electrocardiogram (ECG) is used for the electrical recording of the heart signal. In thispaper, filtering techniques are used for the removal of baseline wander noise, power-line interferencenoise etc. from the ECG signal. Cardiac arrhythmia detection is very useful for the cardiologist foreffective diagnosis of heart functions using ECG. ECG signal analysis involves various techniquesfor accurate delineation of characteristics points and then classification of heart diseases using thesecharacteristics points in terms of positive predictivity and sensitivity. Support vector machine is usedas a classifier to delineate QRS complex.We have reviewed the available techniques for cardiacarrhythmia detection and feature extraction in literature in terms of accuracy and sensitivity. In thispaper, the European database is used for the evaluation of the ST segment. The proposed methodscomprise steps such as signal pre-processing, denoising, QRS complex detection and SVM as aclassifier.
Sunit Kumar, Maneesha Gupta, Amit Kumar Manocha, “Characterization of ST-Segment using Wavelet transforms & Support vector machine”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 1, Issue 7, pp. 13-22, July 2014.
