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Öğe Detection of Position of Replaced Mechanical Heart Valve with ANN(IEEE, 2013) Altunkaya, Sabri; Kara, K.; Gormus, Niyazimechanical heart valve is a device substituted for native heart valve. These valves are generally replaced with mitral or aorta valves. To found whether aorta or mitral heart valve replaced with mechanical one of patients is easy for specialist using stethoscope or chest X-ray. Expert system evaluating mechanical heart valve disease cannot deduce position of replaced heart valve. Thus, we aimed to determine which heart valve of patients was replaced with mechanical one to use preprocessing step in expert systems finding malfunctioning mechanical valve in this study. Electrocardiogram signal and 6 features extracted from power density of heart sounds were used to determine replaced heart valve using artificial neural networks. The heart sounds were separated into four parts according to recording area and sound component. Then, artificial neural networks was separately trained and tested for four sounds using the 6 features. As a result, the mechanical heart valve of patients was detected with 96.55% accuracy from the features of second heart sounds recorded from mitral area.Öğe Dissociable Functional Brain Networks Associated With Apathy in Subcortical Ischemic Vascular Disease and Alzheimer's Disease(Frontiers Media Sa, 2022) Altunkaya, Sabri; Huang, Sheng-Min; Hsu, Yen-Hsuan; Yang, Jir-Jei; Lin, Chien-Yuan; Kuo, Li-Wei; Tu, Min-ChienFew studies have investigated differences in functional connectivity (FC) between patients with subcortical ischemic vascular disease (SIVD) and Alzheimer's disease (AD), especially in relation to apathy. Therefore, the aim of this study was to compare apathy-related FC changes among patients with SIVD, AD, and cognitively normal subjects. The SIVD group had the highest level of apathy as measured using the Apathy Evaluation Scale-clinician version (AES). Dementia staging, volume of white matter hyperintensities (WMH), and the Beck Depression Inventory were the most significant clinical predictors for apathy. Group-wise comparisons revealed that the SIVD patients had the worst level of Initiation by factor analysis of the AES. FCs from four resting state networks (RSNs) were compared, and the connectograms at the level of intra- and inter-RSNs revealed dissociable FC changes, shared FC in the dorsal attention network, and distinct FC in the salient network across SIVD and AD. Neuronal correlates for Initiation deficits that underlie apathy were explored through a regional-specific approach, which showed that the right inferior frontal gyrus, left middle frontal gyrus, and left anterior insula were the critical hubs. These findings broaden the disconnection theory by considering the effect of FC interactions across multiple RSNs on apathy formation.Öğe Paravalvular kaçaklı mekanik kalp kapak ses sinyallerinin ayrık dalgacık dönüşümüyle incelenmesi(2016) Altunkaya, SabriBu çalışmanın amacı mekanik kalp kapak değişiminden sonra kapak kenarında meydana gelen kaçağın belirlenmesine yönelik mekanik kalp kapak ses sinyallerinin ayrık dalgacık dönüşümü ile incelenmesidir. Bu amaçla mekanik kapak kenarında kaçak oluşmuş 2 hasta ile mekanik kalp kapağı normal çalışan 5 hastaya ait kalp kapak ses sinyalleri kayıt edilmiştir. Kayıt edilen mekanik kalp kapak ses sinyalleri ayrık dalgacık dönüşümü ile detay ve yaklaşım katsayılarına ayrıştırılmıştır. Ayrışım sonucu elde edilen detay ve yaklaşım katsayılarından özellikler çıkarılarak normal ve hasta gruba ait özellikler istatistiksel olarak karşılaştırılmıştır. Karşılaştırma sonucunda Daubechies 2 dalgacık fonksiyonundan elde edilen özelliklerin mekanik kalp kapağı kenarında oluşan kaçağın tespitinde kullanılabileceği görülmüştür.Öğe Wavelet Analysis of Mechanical Heart Valve Sounds with Paravalvular Leakage(IEEE, 2014) Altunkaya, Sabri; Kara, Sadik; Gormus, NiyaziDiscrete wavelet transform has been proposed for the diagnosis of paravalvular leakage(PVL) occurs after Mechanical Heart Valve(MHV) replacement. Mechanical heart sounds of 2 patients with PVL and 5 volunteers with normal MHV was recorded and analyzed with different wavelets. As a result, it is statically shown that Daubechies 2 wavelet function is suitable for diagnosis of PVL.
