Detection of ventricular fibrillation based on time domain analysis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, S.-H. | - |
dc.contributor.author | Lim, J.S. | - |
dc.date.available | 2020-02-29T01:41:47Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2013 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/14948 | - |
dc.description.abstract | This study proposes feature extraction using Hilbert transforms and phase space reconstruction to detect ventricular fibrillation (VF) and normal sinus rhythm (NSR) from ECG episodes. We implemented three pre-processing steps to extract features from ECG episodes. In the first step, we use Hilbert transforms to extract peaks. In the second step, we use statistical methods and extract 4 features from the peaks. In the final step, we extract 4 features using statistical methods based on the Euclidean distance between the origin (0, 0) and the peaks after the peaks are plotted in a two dimensional phase space diagram. We applied the 8 features as inputs to a neural network with weighted fuzzy membership functions (NEWFM), and recorded sensitivity, specificity, and accuracy performances of 76.37%, 89.18%, and 86.63%, respectively. © 2013 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.relation.isPartOf | 2013 International Conference on Information Science and Applications, ICISA 2013 | - |
dc.subject | Dimensional phase spaces | - |
dc.subject | Fuzzy membership function | - |
dc.subject | Hilbert transform | - |
dc.subject | NEWFM | - |
dc.subject | Normal sinus rhythm | - |
dc.subject | Phase space reconstruction | - |
dc.subject | Pre-processing step | - |
dc.subject | Ventricular fibrillation | - |
dc.subject | Electrocardiography | - |
dc.subject | Feature extraction | - |
dc.subject | Information science | - |
dc.subject | Statistical methods | - |
dc.subject | Time domain analysis | - |
dc.subject | Phase space methods | - |
dc.title | Detection of ventricular fibrillation based on time domain analysis | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.doi | 10.1109/ICISA.2013.6579507 | - |
dc.identifier.bibliographicCitation | 2013 International Conference on Information Science and Applications, ICISA 2013 | - |
dc.identifier.scopusid | 2-s2.0-84883822176 | - |
dc.citation.title | 2013 International Conference on Information Science and Applications, ICISA 2013 | - |
dc.contributor.affiliatedAuthor | Lim, J.S. | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordAuthor | Hilbert transforms | - |
dc.subject.keywordAuthor | NEWFM | - |
dc.subject.keywordAuthor | Phase space reconstruction | - |
dc.subject.keywordAuthor | Ventricular fibrillation | - |
dc.subject.keywordPlus | Dimensional phase spaces | - |
dc.subject.keywordPlus | Fuzzy membership function | - |
dc.subject.keywordPlus | Hilbert transform | - |
dc.subject.keywordPlus | NEWFM | - |
dc.subject.keywordPlus | Normal sinus rhythm | - |
dc.subject.keywordPlus | Phase space reconstruction | - |
dc.subject.keywordPlus | Pre-processing step | - |
dc.subject.keywordPlus | Ventricular fibrillation | - |
dc.subject.keywordPlus | Electrocardiography | - |
dc.subject.keywordPlus | Feature extraction | - |
dc.subject.keywordPlus | Information science | - |
dc.subject.keywordPlus | Statistical methods | - |
dc.subject.keywordPlus | Time domain analysis | - |
dc.subject.keywordPlus | Phase space methods | - |
dc.description.journalRegisteredClass | scopus | - |
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