EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG

被引：0
|
作者：
Janwattanapong, Panuwat [1 ]
Cabrerizo, Mercedes [1 ]
Rajaei, Hoda [1 ]
Pinzon-Ardila, Alberto [2 ]
Gonzalez-Arias, Sergio [2 ,3 ]
Adjouadi, Malek [1 ]
机构：
[1] Florida Int Univ FIU, Coll Engn & Comp, Ctr Adv Technol & Educ, Dept Elect & Comp Engn, Miami, FL 33199 USA
[2] Baptist Hosp Miami, Baptist Hlth Neurosci Ctr, Miami, FL USA
[3] FIU, Herbert Wertheim Coll Med, Miami, FL USA
来源：
2016 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP) | 2016年
基金：
美国国家科学基金会;
关键词：
Interictal EEG; Functional Connectivity; Patterns Classification; Cross-Correlation; Frequency bands; FUNCTIONAL CONNECTIVITY; NETWORKS; EPILEPSY;
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：
This paper introduces a new method for the quantification and analysis of functional connectivity from electroencephalogram (EEG) by implementing cross correlation method. The recorded clinical EEG signals are segmented and categorized into three types of epileptiform discharges (ED), interictal spike, spike and slow wave complex, and repetitive spike and slow wave complexes. The extracted EEG functional connectivity in different frequency bands were quantified and analyzed to identify characterizing patterns between each type of ED. Results revealed that the number of connections from different epileptogenic biomarkers and calculated for each frequency band were statistically different. Such functional connectivity maps reveal distinctive patterns that can be used to classify these types of ED.
引用
收藏
页码：1161 / 1165
页数：5
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