Classification of migraineurs using functional near infrared spectroscopy data

Date

2012

Author

Sayıta, Yusuf

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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.

Subject Keywords

Migraine., Pattern recognition systems., Near infrared spectroscopy.

URI

http://etd.lib.metu.edu.tr/upload/12614184/index.pdf
https://hdl.handle.net/11511/21347

Collections

Graduate School of Informatics, Thesis