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Full-Text Articles in Physical Sciences and Mathematics
A New Approach For Congestive Heart Failure And Arrhythmia Classification Using Downsampling Local Binary Patterns With Lstm, Süleyman Akdağ, Fatma Kuncan, Yilmaz Kaya
A New Approach For Congestive Heart Failure And Arrhythmia Classification Using Downsampling Local Binary Patterns With Lstm, Süleyman Akdağ, Fatma Kuncan, Yilmaz Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Electrocardiogram (ECG) is a vital diagnosis approach for the rapid explication and detection of various heart diseases, especially cardiac arrest, sinus rhythms, and heart failure. For this purpose, in this study, a different perspective based on downsampling one-dimensional-local binary pattern (1D-DS-LBP) and long short-term memory (LSTM) is presented for the categorization of Electrocardiogram (ECG) signals. A transformation method named 1DDS-LBP has been presented for Electrocardiogram signals. The 1D-DS-LBP method processes the bigness smallness relationship between neighbors. According to the proposed method, by downsampling the signal, the histograms of 1D local binary patterns (1D-LBP) calculated from the obtained signal groups are …
Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Turkish Journal of Electrical Engineering and Computer Sciences
The number of people who die due to cardiovascular diseases is quite high. In our study, ECG (electrocar-diogram) signals were divided into segments and waves based on temporal boundaries. Signal similarity methods such as convolution, correlation, covariance, signal peak to noise ratio (PNRS), structural similarity index (SSIM), one of the basic statistical parameters, arithmetic mean and entropy were applied to each of these sections. In addition, a square error-based new approach was applied and the difference of the signs from the mean sign was taken and used as a feature vector. The obtained feature vectors are used in the artificial …
Probabilistic Dynamic Security Assessment Of Large Power Systems Using Machine Learning Algorithms, Sevda Jafarzadeh, Veysel Murat İstemi̇han Genç
Probabilistic Dynamic Security Assessment Of Large Power Systems Using Machine Learning Algorithms, Sevda Jafarzadeh, Veysel Murat İstemi̇han Genç
Turkish Journal of Electrical Engineering and Computer Sciences
Arrhythmia, also known as dysrhythmia, is a condition involving an irregular heartbeat. A problem in the heart may cause problems in other organs, and as time passes, this will lead to more severe problems. Arrhythmia must be detected at an early stage to prevent such a problem occurring in the heart. Detection of arrhythmia from an electrocardiogram is an easy method that does not need much equipment and does not harm the patient. The purpose of this research is to find a faster and more accurate system to classify nine classes of arrhythmia. The St. Petersburg Institute of Cardiological Technics …
Bagged Tree Classification Of Arrhythmia Using Wavelets For Denoising, Compression, And Feature Extraction, Özgür Tomak, Temel Kayikçioğlu
Bagged Tree Classification Of Arrhythmia Using Wavelets For Denoising, Compression, And Feature Extraction, Özgür Tomak, Temel Kayikçioğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Arrhythmia, also known as dysrhythmia, is a condition involving an irregular heartbeat. A problem in the heart may cause problems in other organs, and as time passes, this will lead to more severe problems. Arrhythmia must be detected at an early stage to prevent such a problem occurring in the heart. Detection of arrhythmia from an electrocardiogram is an easy method that does not need much equipment and does not harm the patient. The purpose of this research is to find a faster and more accurate system to classify nine classes of arrhythmia. The St. Petersburg Institute of Cardiological Technics …
A Comparative Study Of Two Different Fpga-Based Arrhythmia Classifier Architectures, Ahmet Turan Özdemi̇r, Kenan Danişman
A Comparative Study Of Two Different Fpga-Based Arrhythmia Classifier Architectures, Ahmet Turan Özdemi̇r, Kenan Danişman
Turkish Journal of Electrical Engineering and Computer Sciences
Early diagnosis of dangerous heart conditions is very important for the treatment of heart diseases and for the prevention of sudden cardiac death. Automatic electrocardiogram (ECG) arrhythmia classifiers are essential to timely diagnosis. However, most of the medical diagnosis systems proposed in the literature are software-based. This work focused on the hardware implementation of a mobile artificial neural network (ANN)-based arrhythmia classifier that is implemented on a field programmable gate array (FPGA) as a single chip solution, as an alternative to various software models of ANNs. Due to the parallel nature of ANNs, hardware implementation of ANNs needs a large …
Fully Parallel Ann-Based Arrhythmia Classifier On A Single-Chip Fpga: Fpaac, Ahmet Turan Özdemi̇r, Kenan Danişman
Fully Parallel Ann-Based Arrhythmia Classifier On A Single-Chip Fpga: Fpaac, Ahmet Turan Özdemi̇r, Kenan Danişman
Turkish Journal of Electrical Engineering and Computer Sciences
Recognition of cardiac arrhythmias by electrocardiogram (ECG) is an important issue for diagnosis of cardiac abnormalities. Many studies on recognition of cardiac arrhythmias by ECG, using various techniques, have been performed in the past 20 years. Artificial neural networks (ANNs) are the most widely used tool in medical diagnosis systems (MDS) because of their powerful prediction characteristics. An ANN model is inspired by real biological neural networks, with a parallel structure that is potentially fast for computation. However, the suggested ANN architectures in the literature can only be run sequentially, on powerful processors, due to their complexity. Our approach enables …