Abstract:
In last decades, optical imaging technology has been rapidly developed and become much popular for scientific researches. Its safe, non-invasive and portable design easily integrates fNIRS to different research areas and makes it much preferable especially for brain researchers. Since fNIRS sensitively scan neurobiological changes in the PFC during neurological and psychiatric disorders, many studies benefits from the convenience of fNIRS to extend the understanding about these disorders. This study aims to present reflections of different PFC related disorders which are schizophrenia, migraine and attention deficit & hyperactivity disorder (ADHD) on fNIRS measurements and to reveal their differences from control group via advanced signal processing application. For this purpose, collected fNIRS measurements during cognitive task were preprocessed to remove artifacts and prepared for further analysis. Pre-processed signal sets were used to create feature set for each subject with the assistance of independent component analysis. Then these feature sets were investigated by clustering algorithm to observe discrimination of experimental groups and performance of the system was reported. In some cases, proposed system presents success rates up to 82% for migraine group, 92% for schzophrenia group and 95% ADHD group.|Keywords : fNIRS, Signal Processing, Schizophrenia, Migraine, Attention Deficit & Hyperactivity Disorder, Independent Component Analysis ,Clustering
