Application of Machine Learning Methods for Artificial ECG with T-wave alternans

Autor: Oleksandra Karnaukh, Yevgeniy Karplyuk

Publikováno v: 2020 IEEE 40th International Conference on Electronics and Nanotechnology (ELNANO).

This paper presents the modeling approach artificial electrocardiograms (ECG) with T -wave alternans based on extracted parameters from the T -wave alternas (TWA) database. The developed optimal TWA classification system was evaluated by signals from

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::15b6bbb2ce6634cddba17a7c6a588b4e
https://doi.org/10.1109/elnano50318.2020.9088826

Modeling of ECG and creation artificial database with synthetic T-wave alternans

Autor: Yevgeniy Karplyuk, Oleksandra Karnaukh

Publikováno v: 2019 IEEE 39th International Conference on Electronics and Nanotechnology (ELNANO).

This paper presents the electrocardiogram (ECG) modeling approach with different level of T-wave alternans (TWA). To create a variety of signals, 17 parameters were used, where three parameters were changed to create a signal with different level and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2130851cd270aee32e5bc10149a8429c
https://doi.org/10.1109/elnano.2019.8783492

Machine learning techniques application for lung diseases diagnosis

Autor: Yevgeniy Karplyuk, Valentyn Vaityshyn, Anna Poreva

Publikováno v: 2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE).

The article considers the basic methods of machine learning for applying them to the task of the lungs sounds classifying. A number of signal parameters were obtained on the basis of the lungs sounds set. The task of the study was to classify sounds

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1f218ac3f370b615a63d39eda255a515
https://doi.org/10.1109/aieee.2017.8270528

Identification and Assessment of Electrocardiographic Markers of Cardiac Electrical Instability

Autor: Yevgeniy Karplyuk, Kateryna Ivanko, Nataliia Ivanushkina

Publikováno v: Наукові вісті КПІ; № 1 (2017): ; 37-47
Научные вести КПИ; № 1 (2017): ; 37-47
Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute"; № 1 (2017): Engineering; 37-47
"Research Bulletin of the National Technical University of Ukraine ""Kyiv Politechnic Institute"""
"""Research Bulletin of the National Technical University of Ukraine """"Kyiv Politechnic Institute"""""""
Наукові вісті НТУУ «КПІ» : міжнародний науково-технічний журнал, 2017, № 1(111)

Background. Development of the methods for identification and assessment of early signs of heart disorders makes it possible to catch the sight of disease at its initial stage. The article considers the methods of early diagnosis of the cardiovascula

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99541590536ca15baa18760c8216051a
http://bulletin.kpi.ua/article/view/91386

Application of higher-order spectral analysis to lung sounds in patients with chronic bronchitis

Autor: Yevgeniy Karplyuk, Anastasiia Makarenkova, Anna Poreva, Mariia Chekhovych

Publikováno v: 2016 IEEE 36th International Conference on Electronics and Nanotechnology (ELNANO).

This article describes a method that allows to classify lung sounds by the category of healthy patient and patient with bronchitis. The method is based on the use of apparatus of higher-order statistics, namely on calculating of skewness and kurtosis

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::09f37866423983cf426fbbd3add15007
https://doi.org/10.1109/elnano.2016.7493059