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- Publisher Website: 10.1109/APBME.2003.1302613
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Conference Paper: Multi-channel Fourier packet transform of EEG: optimal representation and time-varying coherence
Title | Multi-channel Fourier packet transform of EEG: optimal representation and time-varying coherence |
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Authors | |
Keywords | EEG ERP Fourier Packet Coherence |
Issue Date | 2003 |
Publisher | IEEE. |
Citation | IEEE - E M B S Asian-Pacific Conference on Biomedical Engineering, Kyoto-Osaka-Nara, JAPAN, 20-22 October 2003, p. 120-121 How to Cite? |
Abstract | Multi-channel recording of electroencephalogram (EEG) provides a measure of spatial-temporal pattern of cognitive processes. When oscillatory activities are going to be studied, the time-domain EEG signal can be analyzed via Fourier or wavelet transform. However the loss of temporal information after Fourier transform and the unavailability of phase information in wavelet transform limit their applicability in EEG analysis. In this paper, multi-channel Fourier packet transform is introduced. The algorithm resembles the wavelet packet transform by its binary tree search for an optimal selection of orthogonal basis, but extends the application to the multi-channel scenario. It aims to provide a sparse signal representation to localize features in the spatial-spectral-temporal domain. Since the decomposed atoms are spatially coherent components, analysis of time-varying synchrony across scalp locations is then possible. |
Persistent Identifier | http://hdl.handle.net/10722/46514 |
DC Field | Value | Language |
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dc.contributor.author | Ting, KH | en_HK |
dc.contributor.author | Shen, M | en_HK |
dc.contributor.author | Fung, PCW | en_HK |
dc.contributor.author | Chan, FHY | en_HK |
dc.date.accessioned | 2007-10-30T06:51:40Z | - |
dc.date.available | 2007-10-30T06:51:40Z | - |
dc.date.issued | 2003 | en_HK |
dc.identifier.citation | IEEE - E M B S Asian-Pacific Conference on Biomedical Engineering, Kyoto-Osaka-Nara, JAPAN, 20-22 October 2003, p. 120-121 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/46514 | - |
dc.description.abstract | Multi-channel recording of electroencephalogram (EEG) provides a measure of spatial-temporal pattern of cognitive processes. When oscillatory activities are going to be studied, the time-domain EEG signal can be analyzed via Fourier or wavelet transform. However the loss of temporal information after Fourier transform and the unavailability of phase information in wavelet transform limit their applicability in EEG analysis. In this paper, multi-channel Fourier packet transform is introduced. The algorithm resembles the wavelet packet transform by its binary tree search for an optimal selection of orthogonal basis, but extends the application to the multi-channel scenario. It aims to provide a sparse signal representation to localize features in the spatial-spectral-temporal domain. Since the decomposed atoms are spatially coherent components, analysis of time-varying synchrony across scalp locations is then possible. | en_HK |
dc.format.extent | 210170 bytes | - |
dc.format.extent | 13817 bytes | - |
dc.format.extent | 3485 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | text/plain | - |
dc.format.mimetype | text/plain | - |
dc.language | eng | en_HK |
dc.publisher | IEEE. | en_HK |
dc.rights | ©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.subject | EEG | en_HK |
dc.subject | ERP | en_HK |
dc.subject | Fourier Packet | en_HK |
dc.subject | Coherence | en_HK |
dc.title | Multi-channel Fourier packet transform of EEG: optimal representation and time-varying coherence | en_HK |
dc.type | Conference_Paper | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.doi | 10.1109/APBME.2003.1302613 | en_HK |
dc.identifier.scopus | eid_2-s2.0-84866784442 | - |
dc.identifier.hkuros | 96199 | - |