Classification of migraineurs using functional near infrared spectroscopy data

Sayıta, Yusuf
Classification of migraineur and healthy subjects using statistical pattern classifiers on functional Near Infrared Spectroscopy (NIRS) data is the main purpose of this study. Also a statistical comparison between trials that have different type of classifiers, classifier settings and feature sets is done. Features are extracted from raw light measurement data acquired with NIRS device, namely Niroxcope, during two separate previous studies, using Modified Beer-Lambert Law. After feature extraction, Naïve Bayes classifier and k Nearest Neighbor classifier are utilized with and with-out Principal Component Analysis in separate trials. Results obtained are compared within each other using statistical hypothesis tests namely Mc Nemar and Cochran Q.


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Recognition of the the cognitive states by using functional Magnetic Rezonans Imaging (fMRI) data is a challenging problem that has been a focus of scientific research for a long time. In this study the effectiveness of clustering and the ensemble learning techniques on fMRI dataset is investigated and different paramaters are compared. Moreover, the performance of these techniques are tested on both raw voxel intensity values and meshes formed by multiple voxels. Clusters are compared to the functional bra...
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TOKSÖZ, Mehmet Altan; Ulusoy, İlkay (Institution of Engineering and Technology (IET), 2016-08-01)
The authors present a sparsity-based algorithm, basic thresholding classifier (BTC), for classification applications which is capable of identifying test samples extremely rapidly and performing high classification accuracy. They introduce a sufficient identification condition (SIC) under which BTC can identify any test sample in the range space of a given dictionary. By using SIC, they develop a procedure which provides a guidance for the selection of threshold parameter. By exploiting rapid classification...
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This paper presents a classification method for hyperspectral images utilizing Differential Morphological Profiles (DMPs) which permit to include in the analysis spatial information since they can provide an estimate of the size and contrast characteristics of the structures in an image. Due to the wide variety of objects present in a scene, the pixels belonging to the same semantic structure may not have homogeneous spatial and spectral features. In addition, instead of a single peak (which can be related ...
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Çakır, Murat Perit; Girisken, Yener; Yurdakul, Dicle (2018-01-01)
Purpose This study aims to explore the plausibility of the functional near-infrared spectroscopy (fNIRS) methodology for neuromarketing applications and develop a neurophysiologically-informed model of purchasing behavior based on fNIRS measurements.
Design and Optimization of Nanoantennas for Nano-Optical Applications
Işıklar, Göktuğ; Ergül, Özgür Salih; Department of Electrical and Electronics Engineering (2020-9)
In this study, design and simulation of plasmonic nanoantenna structures to obtain high power enhancement capabilities at optical frequencies, as well as utilization of nanoantennas for imaging and sensing applications are presented. Plasmonic characteristics of nanoantennas, which depend on many parameters, such as material, frequency, geometry, and size, are investigated in detail via computational analyses of various nanoantenna structures. Numerical solutions of electromagnetic problems are performe...
Citation Formats
Y. Sayıta, “Classification of migraineurs using functional near infrared spectroscopy data,” M.S. - Master of Science, Middle East Technical University, 2012.