R-peaks Detection with Convolutional Neural Network in Electrocardiogram Signal
BildiriYalnız künye
Özet
The performance of electrocardiogram applications is closely related to the succesful detection of R-peaks. Therefore, successful detection of R-peaks is of high importance. Electrocardiogram signals vary from person to person, so detection of R-peaks is getting difficult. In this study, Evolutionary Neural Network which is a deep learning model and imitates human vision, is used to detect R-peaks. The MIT-BIH Arrhythmia Database with 48 different records was used as the database and experimental results with very high accuracy were obtained.
Anahtar Kelimeler
RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/15921Resmi atıflarda kullanılan kalıcı adresTam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.contributor.author | Dogan, Ramazan Ozgur | |
| dc.contributor.author | Kayikçioglu, Temel | |
| dc.contributor.other | IEEE | |
| dc.date.accessioned | 2026-10-22T10:26:13.317465579Z | |
| dc.date.available | 2026-10-22T10:26:13.317465579Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | The performance of electrocardiogram applications is closely related to the succesful detection of R-peaks. Therefore, successful detection of R-peaks is of high importance. Electrocardiogram signals vary from person to person, so detection of R-peaks is getting difficult. In this study, Evolutionary Neural Network which is a deep learning model and imitates human vision, is used to detect R-peaks. The MIT-BIH Arrhythmia Database with 48 different records was used as the database and experimental results with very high accuracy were obtained. | |
| dc.identifier.isbn | 978-1-5386-1501-0 | |
| dc.identifier.issn | 2165-0608 | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/gumushane/15921 | |
| dc.identifier.wos | WOS:000511448500508 | |
| dc.language.iso | tr | |
| dc.publisher | IEEE | |
| dc.relation.conference | 26th IEEE Signal Processing and Communications Applications Conference (SIU) | |
| dc.relation.ispartof | 2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | ECG | |
| dc.subject | Convolutional Neural Network | |
| dc.subject | R-peaks | |
| dc.subject.classification | Engineering, Electrical & Electronic | |
| dc.subject.classification | Telecommunications | |
| dc.subject.classification | Engineering | |
| dc.title | R-peaks Detection with Convolutional Neural Network in Electrocardiogram Signal | |
| dc.type | Conference Object | |
| dspace.entity.type | Publication | |
| rdl.citation.wos | 0 | |
| rdl.conference.date | MAY 02-05, 2018 | |
| rdl.conference.place | Izmir, TURKEY | |
| rdl.oa.status | closed | |
| rdl.source.index | WOS | |
| rdl.wos.index | Conference Proceedings Citation Index - Science (CPCI-S) |
