Early prediction of Paroxysmal Atrial Fibrillation using frequency domain measures of heart rate variability

Narin, Ali | İşler, Yalçın | Özer, Mahmut

Proceedings | 2017 | 2016 Medical Technologies National Conference, TIPTEKNO 2016

Paroxysmal Atrial Fibrillation (PAF) is a very common heart disease caused by irregular impulses of atrial tissue in adult. Diagnosing in the early stages of this disorder is very important for the patients to stop the progression of the disease and to improve the life quality. In this study, it is aimed to predict the PAF event before the realization of the PAF which in 5 minutes for the PAF patients. 30-minute data used in the study were divided into 5-minute parts. Fast Fourier Transform of frequency domain measures of heart rate variability obtained easily and practically is used for each part. The statistical significances amon . . .g segments and discriminating performances of k-Nearest Neighbors classifier were obtained for each segment using these measurements. Consequently, As a result of statistical analysis, it is shown that patients may be warned 12.5 minutes earlier than a PAF attack. © 2016 IEEE Daha fazlası Daha az

Effects of synaptic heterogenity on vibrational resonance in biological neural networks

Ağaoğlu, Şükrüye Nihal | Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

Proceedings | 2017 | 2016 Medical Technologies National Conference, TIPTEKNO 2016

In this study, vibrational resonance phenomena is investigated for topologies of scale-free network in excitable neural system. Effect of heterogeneity which emerges from weightening synaptic conductivity in neural network on performance of weak signal detection is studied. FitzHugh-Nagumo neuron model with electrical coupling is used as excitable system. In the result of numerical simulations; it is seen that the state of the scale-free network being unweighted or weighted, synaptic conductivity and average connectivity degree play a crucial role for determining performance of information coding of neuron population based on vibrat . . .ional resonance. © 2016 IEEE Daha fazlası Daha az

Determination of the physiological effects of diabetic retinopathy disease from Video-Oculography (VOG) signals using discrete wavelet transform

Kaya, Ceren | Erkaymaz, Okan | Ayar, Orhan | Özer, Mahmut

Proceedings | 2017 | 2016 Medical Technologies National Conference, TIPTEKNO 2016

The insulin hormone secreted from the pancreas gland in the body is not present in sufficient amount, or because they do not fit, which is defined as the elevation of blood glucose 'Diabetes Mellitus (Diabetes)'. 'Diabetic Retinopathy' is the most common in diabetes-related eye diseases. It had done damages in the retina that detect light on behind the eye as a result of changes in the arteries that is one of the reasons that makes blindness (loss of vision) in people. In this study, horizontal and vertical Video-Oculography (VOG) signals captured by using internal tracking camera in Metrovision MonPackOne Electrooculography device. . . . In order to filter the noise from the signals, the wavelet transform method was used. Obtained signals have shown that the signals of diabetic retinopathy patients have higher amplitude and irregular characteristic than the signals obtained from healthy groups. In both groups, significant Daubechies-6 wavelet coefficients (A6-D6) gave better results than Daubechies-4 wavelet coefficients (A4-D4). Obtained data as a result of using wavelet transform sheds light on feature extraction and classification in proposed future works. © 2016 IEEE Daha fazlası Daha az

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