Automatic Noise Removal and Phase Synchronization for MI EEG Analysis - Hsu, Wei-Yen
24,99 €
inkl. MwSt.

Versandfertig in über 4 Wochen
  • Broschiertes Buch

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…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
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.
Autorenporträt
He received the MS and PhD degrees in the Department of Computer Science and Information Engineering from National Cheng Kung University, Tainan, Taiwan in 2001 and 2008, respectively. His current research interests include medical image processing, biomedical signal processing, neuroscience methods, and computer vision and graphics.