Residential College | false |
Status | 已發表Published |
Detection of Attention-to-Rest Transition from EEG Signals with the Help of Empirical Mode Decomposition | |
Ng C.M.; Vai M.I. | |
2011-12-01 | |
Conference Name | International Conference on Intelligent Computing and Information Science |
Source Publication | Communications in Computer and Information Science |
Volume | 135 |
Issue | PART 2 |
Pages | 66-71 |
Conference Date | JAN 08-09, 2011 |
Conference Place | Chongqing, PEOPLES R CHINA |
Abstract | In this paper, an empirical mode decomposition (EMD) scheme is applied to analyze the steady-state visually evoked potentials (SSVEP) in electroencephalogram (EEG). Based on EMD method, the oscillatory activities of the decomposed SSVEP signal are analyzed. It is observed that the 6th IMF showed the features of the attention-to-rest transition response. In other words, high powers are observed instantly after the volunteer turns from an attentively focusing stage into an unfocused attention stage. Having made the point that the 6th IMF of the SSVEP signals corresponds to very low frequency (0.5 - 2 Hz), this drives us to look into that frequency range of the SSVEP signal. All of this reflects that a very low frequency seems to occur during the attention-to-rest transitions. Experiments are performed with different people. The result shows that the attention-to-rest transition can be detected with an accuracy of 82.6%. © Springer-Verlag Berlin Heidelberg 2011. |
Keyword | Electroencephalogram (Eeg) Empirical Mode Decomposition (Emd) Intrinsic Mode Functions (Imf) Steady-state Visually Evoked Potentials (Ssvep) |
DOI | 10.1007/978-3-642-18134-4_11 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science |
WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods |
WOS ID | WOS:000288681600011 |
Scopus ID | 2-s2.0-84880726316 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING |
Corresponding Author | Ng C.M. |
Affiliation | Universidade de Macau |
First Author Affilication | University of Macau |
Corresponding Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Ng C.M.,Vai M.I.. Detection of Attention-to-Rest Transition from EEG Signals with the Help of Empirical Mode Decomposition[C], 2011, 66-71. |
APA | Ng C.M.., & Vai M.I. (2011). Detection of Attention-to-Rest Transition from EEG Signals with the Help of Empirical Mode Decomposition. Communications in Computer and Information Science, 135(PART 2), 66-71. |
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