Feature Extraction of Electroencephalography Based on LASSO-Granger Causality Between Brain Region of Interest

SHE Qingshan; CHEN Xihao; GAO Farong; LUO Zhizeng

doi:10.11999/JEIT150851

Volume 38 Issue 5

May 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(5): 1266-1270

SHE Qingshan, CHEN Xihao, GAO Farong, LUO Zhizeng. Feature Extraction of Electroencephalography Based on LASSO-Granger Causality Between Brain Region of Interest[J]. Journal of Electronics & Information Technology, 2016, 38(5): 1266-1270. doi: 10.11999/JEIT150851

Citation:

SHE Qingshan, CHEN Xihao, GAO Farong, LUO Zhizeng. Feature Extraction of Electroencephalography Based on LASSO-Granger Causality Between Brain Region of Interest[J]. Journal of Electronics & Information Technology, 2016, 38(5): 1266-1270. doi: 10.11999/JEIT150851

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Feature Extraction of Electroencephalography Based on LASSO-Granger Causality Between Brain Region of Interest

doi: 10.11999/JEIT150851

Funds:

The National Natural Science Foundation of China (61201302, 61172134), State Scholarship Fund of China (201308330297), Natural Science Foundation of Zhejiang Province (LY15F010009)

Received Date: 2015-07-16
Rev Recd Date: 2016-01-29
Publish Date: 2016-05-19

Abstract

Abstract

Brain functional network is introduced to feature extraction of ElectroEncephaloGraphy (EEG), and a novel method is proposed based on Least Absolute Shrinkage and Selection Operator (LASSO)-Granger causality between Region Of Interest (ROI) in the brain, in order to overcome the inherent deficiencies of research methods based on isolated brain region. Firstly, the maximum principal component of ROIs is extracted by Principal Component Analysis (PCA), and then causality values between ROIs are calculated by LASSO-Granger. Finally, the values are used as the input vector for Support Vector Machine (SVM), and then four datasets of BCI Competition IV Dataset 1 are used for classification．Experimental results show that different motor imagery tasks are successfully identified by the method of SVM classifier combined with feature extraction which is based on LASSO-Granger causality between the brain region of interest (ROIs). This method provides a new idea for the study of extracting EEG features.
- Brain functional network,
- LASSO-Granger,
- Region Of Interest (ROI),
- Feature extraction

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