FILTERING OF FUNCTIONAL NEAR INFRARED SPECTROSCOPY SIGNALS BY EIGENVALUE BASED METHODS

被引：0
|
作者：
Eken, Aykut [1 ]
机构：
[1] Orta Dogu Tekn Univ, Enformat Enstitusu, Med Enformat Ana Bilim Dali, Ankara, Turkey
来源：
2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2014年
关键词：
fNIRS; tSVD; PCA; AR Power Spectrum;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Functional Near Infrared Spectroscopy is used in neuroimaging studies to observe the oxyhemoglobin (HB02) 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.
引用
收藏
页码：373 / 376
页数：4
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