Yazar "Tagluk, M. Emin" seçeneğine göre listele

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    Classification of sleep apnea by using wavelet transform and artificial neural networks
    (Pergamon-Elsevier Science Ltd, 2010) Tagluk, M. Emin; Akin, Mehmet; Sezgin, Nemettin
    This paper describes a new method to classify sleep apnea syndrome (SAS) by using wavelet transforms and an artificial neural network (ANN) The network was trained and tested for different momentum coefficients. The abdominal respiration signals are separated into spectral components by using multi-resolution wavelet transforms. These spectral components are applied to the inputs of the artificial neural network. Then the neural network was configured to give three outputs to classify the SAS situation of the patient. The apnea can be broadly classified into three types. obstructive sleep apnea (OSA), central sleep apnea (CSA) and mixed sleep apnea (MSA). During OSA. the airway is blocked while respiratory efforts continue. During CSA the airway is open. however, there are no respiratory efforts In this paper we aim to classify sleep apnea in one of three basic types: obstructive, central and mixed. (C) 2009 Elsevier Ltd. Ail rights reserved.
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    Estimation of Sleep Stages by an Artificial Neural Network Employing EEG, EMG and EOG
    (Springer, 2010) Tagluk, M. Emin; Sezgin, Necmettin; Akin, Mehmet
    Analysis and classification of sleep stages is essential in sleep research. In this particular study, an alternative system which estimates sleep stages of human being through a multi-layer neural network (NN) that simultaneously employs EEG, EMG and EOG. The data were recorded through polisomnography device for 7 h for each subject. These collective variant data were first grouped by an expert physician and the software of polisomnography, and then used for training and testing the proposed Artificial Neural Network (ANN). A good scoring was attained through the trained ANN, so it may be put into use in clinics where lacks of specialist physicians.
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    Time-Frequency analysis of Snoring Sounds in Patients With Simple Snoring And OSAS
    (Ieee, 2009) Tagluk, M. Emin; Akin, Mehmet; Sezgin, Necmettin
    In recent years variety of studies has been conducted towards the identification of correlation between Obstructive Sleep Apnea Syndrome (OSAS) and snoring. The features defected from time and frequency domain analysis of snores showed the differences between simple and OSAS patients. In this study the total episodes of 1500 snore records taken from 7 simple and 14 OSAS patients were evaluated through time-frequency analysis. From the time-frequency analysis the differences, particularly from the spectral bandwidth point of view, between the two groups were identified, and using this data the method was suggested as a cost effective and simple technique to be widely used in defection of OSAS from simple patients.