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Inhaltsangabe
1. In this book, a novel brain-computer interface (BCI) system is proposed to analyze motor imagery (MI) electroencephalogram (EEG) signals. 2. After eliminating EOG artifacts automatically and extracting features by wavelet-based phase synchronization approach, support vector machine (SVM) is adopted for the classification of single-trial left and right MI data. 3. The EOG artifacts are automatically removed by means of modified independent component analysis (ICA). 4. The features are extracted from wavelet data by phase synchronization, and then classified by the SVM. 5. Compared with the results without EOG artifact removal, spectral band and AR model features, the proposed system achieves satisfactory results in BCI applications.
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Reseña del editor
1. In this book, a novel brain-computer interface (BCI) system is proposed to analyze motor imagery (MI) electroencephalogram (EEG) signals. 2. After eliminating EOG artifacts automatically and extracting features by wavelet-based phase synchronization approach, support vector machine (SVM) is adopted for the classification of single-trial left and right MI data. 3. The EOG artifacts are automatically removed by means of modified independent component analysis (ICA). 4. The features are extracted from wavelet data by phase synchronization, and then classified by the SVM. 5. Compared with the results without EOG artifact removal, spectral band and AR model features, the proposed system achieves satisfactory results in BCI applications.
Biografía del autor
Wei-Yen Hsu received the Ph.D. degree in the Department of CSIE, National Cheng Kung University, Tainan, Taiwan, in 2008. He is an assistant professor in the Department of Information Management, National Chung Cheng University now. His research interests include medical image processing, biomedical signal processing and neuroscience methods.
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Automatic Noise Removal and Phase Synchronization for MI EEG Analysis
Verlag:
LAP LAMBERT Academic Publishing Apr 2013, 2013
ISBN 10: 3659382434
ISBN 13: 9783659382437
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Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -1. In this book, a novel brain-computer interface (BCI) system is proposed to analyze motor imagery (MI) electroencephalogram (EEG) signals. 2. After eliminating EOG artifacts automatically and extracting features by wavelet-based phase synchronization approach, support vector machine (SVM) is adopted for the classification of single-trial left and right MI data. 3. The EOG artifacts are automatically removed by means of modified independent component analysis (ICA). 4. The features are extracted from wavelet data by phase synchronization, and then classified by the SVM. 5. Compared with the results without EOG artifact removal, spectral band and AR model features, the proposed system achieves satisfactory results in BCI applications.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch. Artikel-Nr. 9783659382437
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