CARDIAC ARRHYTHMIA DIAGNOSIS USING A NEURO-FUZZY APPROACH
| dc.contributor.author | Benali, R | en_US |
| dc.contributor.author | Dib, N | en_US |
| dc.contributor.author | Beriksi Reguig, F | en_US |
| dc.date.accessioned | 2013-06-06T13:47:03Z | en_US |
| dc.date.available | 2013-06-06T13:47:03Z | en_US |
| dc.date.issued | 2010-09 | en_US |
| dc.description | Journal of Mechanics in Medicine and Biology , ISSN : 0219-5194, DOI : 10.1142/S021951941000354X, Issue : 3, Volume : 10, pp. 417-429, September 2010. | en_US |
| dc.description.abstract | The ventricular premature contractions (VPC) are cardiac arrhythmias that are widely encountered in the cardiologic field. They can be detected using the electrocardiogram (ECG) signal parameters. A novel method for detecting VPC from the ECG signal is proposed using a new algorithm (Slope) combined with a fuzzy-neural network (FNN). To achieve this objective, an algorithm for QRS detection is first implemented, and then a neuro-fuzzy classifier is developed. Its performances are evaluated by computing the percentages of sensitivity (SE), specificity (SP), and correct classification (CC). This classifier allows extraction of rules (knowledge base) to clarify the obtained results. We use the medical database (MIT-BIH) to validate our results. | en_US |
| dc.identifier.issn | 0219-5194 | en_US |
| dc.identifier.uri | https://dspace.univ-tlemcen.dz/handle/112/1967 | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | University of Tlemcen | en_US |
| dc.subject | ECG QRS detection | en_US |
| dc.subject | neuro-fuzzy | en_US |
| dc.subject | fuzzy logic | en_US |
| dc.subject | VPC | en_US |
| dc.subject | explicit classification | en_US |
| dc.subject | MIT-BIH database | en_US |
| dc.title | CARDIAC ARRHYTHMIA DIAGNOSIS USING A NEURO-FUZZY APPROACH | en_US |
| dc.type | Article | en_US |