Yazarlar
Yayınlar
- BildiriYalnız künye2018R-peaks Detection with Convolutional Neural Network in Electrocardiogram Signal
Dogan, Ramazan Ozgur; Kayikçioglu, Temel
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.
- BildiriYalnız künye2018Detecting Cardiac Arrhythmia by Using Time Differences of Double Wavelength PPG Peaks
Yildirim, Omer; Kayikçioglu, Temel
Nowadays, photopletismogram (PPG) signals are used in respiration and blood pressure measurement, monitoring of the sleep pattern and also detecting of mental disorders, mainly blood oxygen saturation and heartrate measurement. The reason of the use of PPG signals instead of signals such as electroencephalogram (EEG) or electrocardiogram (ECG) is easy to obtain and real-time monitoring of these data, as well as being easily used by people in daily life and easily integrated into wearable technologies. In this study, detecting of cardiac arrhythmia was made successfully by using double wavelength PPG signals instead of ECG signals