Title :
Filtering of functional near infrared spectroscopy signals by eigenvalue based methods
Author_Institution :
Enformatik Enstitusu, Med. Enformatik Ana Bilim Dali, Orta Dogu Teknik Univ., Ankara, Turkey
Abstract :
Functional Near Infrared Spectroscopy is used in neuroimaging studies to observe the oxyhemoglobin (HBO2) and deoxyhemoglobin (HB) changes. Blood oxygen level dependency (BOLD) signal that is collected by using this system shows response in related region in brain against an applied stimulus. Therefore in these signals, signal to noise ratio (SNR) is quite important to decide the behavior of brain in related region In this study, fNIRS data was filtered by using eigenvalue based methods such as Principal Component Analysis (PCA) and Truncated Singular Value Decomposition (tSVD). Using SNR and Autoregressive (AR) power spectrum performance results were compared.
Keywords :
eigenvalues and eigenfunctions; filtering theory; medical signal processing; principal component analysis; singular value decomposition; BOLD signal; PCA; blood oxygen level dependency signal; eigenvalue based methods; fNIRS data; functional near infrared spectroscopy signals; neuroimaging studies; principal component analysis; signal filtering; tSVD; truncated singular value decomposition; Art; Conferences; Matrix decomposition; Principal component analysis; Signal to noise ratio; Spectroscopy; AR Power Spectrum; PCA; fNIRS; tSVD;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location :
Trabzon
DOI :
10.1109/SIU.2014.6830243
