Hilbert-Huang transformation-based time-frequency analysis methods in biomedical signal applications.
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| Title: | Hilbert-Huang transformation-based time-frequency analysis methods in biomedical signal applications. |
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| Authors: | Lin CF (AUTHOR), Zhu JD (AUTHOR), Lin, Chin-Feng1 (AUTHOR), Zhu, Jin-De (AUTHOR) |
| Source: | Proceedings of the Institution of Mechanical Engineers -- Part H -- Journal of Engineering in Medicine (Professional Engineering Publishing). 2012 Mar, Vol. 226 Issue 3, p208-216. 9p. |
| Abstract: | Hilbert-Huang transformation, wavelet transformation, and Fourier transformation are the principal time-frequency analysis methods. These transformations can be used to discuss the frequency characteristics of linear and stationary signals, the time-frequency features of linear and non-stationary signals, the time-frequency features of non-linear and non-stationary signals, respectively. The Hilbert-Huang transformation is a combination of empirical mode decomposition and Hilbert spectral analysis. The empirical mode decomposition uses the characteristics of signals to adaptively decompose them to several intrinsic mode functions. Hilbert transforms are then used to transform the intrinsic mode functions into instantaneous frequencies, to obtain the signal's time-frequency-energy distributions and features. Hilbert-Huang transformation-based time-frequency analysis can be applied to natural physical signals such as earthquake waves, winds, ocean acoustic signals, mechanical diagnosis signals, and biomedical signals. In previous studies, we examined Hilbert-Huang transformation-based time-frequency analysis of the electroencephalogram FPI signals of clinical alcoholics, and 'sharp I' wave-based Hilbert-Huang transformation time-frequency features. In this paper, we discuss the application of Hilbert-Huang transformation-based time-frequency analysis to biomedical signals, such as electroencephalogram, electrocardiogram signals, electrogastrogram recordings, and speech signals. [ABSTRACT FROM AUTHOR] |
| Copyright of Proceedings of the Institution of Mechanical Engineers -- Part H -- Journal of Engineering in Medicine (Professional Engineering Publishing) is the property of Professional Engineering Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 108186390 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Hilbert-Huang transformation-based time-frequency analysis methods in biomedical signal applications. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lin+CF%22">Lin CF</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhu+JD%22">Zhu JD</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lin%2C+Chin-Feng%22">Lin, Chin-Feng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhu%2C+Jin-De%22">Zhu, Jin-De</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Proceedings+of+the+Institution+of+Mechanical+Engineers+--+Part+H+--+Journal+of+Engineering+in+Medicine+%28Professional+Engineering+Publishing%29%22">Proceedings of the Institution of Mechanical Engineers -- Part H -- Journal of Engineering in Medicine (Professional Engineering Publishing)</searchLink>. 2012 Mar, Vol. 226 Issue 3, p208-216. 9p. – Name: Abstract Label: Abstract Group: Ab Data: Hilbert-Huang transformation, wavelet transformation, and Fourier transformation are the principal time-frequency analysis methods. These transformations can be used to discuss the frequency characteristics of linear and stationary signals, the time-frequency features of linear and non-stationary signals, the time-frequency features of non-linear and non-stationary signals, respectively. The Hilbert-Huang transformation is a combination of empirical mode decomposition and Hilbert spectral analysis. The empirical mode decomposition uses the characteristics of signals to adaptively decompose them to several intrinsic mode functions. Hilbert transforms are then used to transform the intrinsic mode functions into instantaneous frequencies, to obtain the signal's time-frequency-energy distributions and features. Hilbert-Huang transformation-based time-frequency analysis can be applied to natural physical signals such as earthquake waves, winds, ocean acoustic signals, mechanical diagnosis signals, and biomedical signals. In previous studies, we examined Hilbert-Huang transformation-based time-frequency analysis of the electroencephalogram FPI signals of clinical alcoholics, and 'sharp I' wave-based Hilbert-Huang transformation time-frequency features. In this paper, we discuss the application of Hilbert-Huang transformation-based time-frequency analysis to biomedical signals, such as electroencephalogram, electrocardiogram signals, electrogastrogram recordings, and speech signals. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Proceedings of the Institution of Mechanical Engineers -- Part H -- Journal of Engineering in Medicine (Professional Engineering Publishing) is the property of Professional Engineering Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 208 Titles: – TitleFull: Hilbert-Huang transformation-based time-frequency analysis methods in biomedical signal applications. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lin CF – PersonEntity: Name: NameFull: Zhu JD – PersonEntity: Name: NameFull: Lin, Chin-Feng – PersonEntity: Name: NameFull: Zhu, Jin-De IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: 2012 Mar Type: published Y: 2012 Identifiers: – Type: issn-print Value: 09544119 Numbering: – Type: volume Value: 226 – Type: issue Value: 3 Titles: – TitleFull: Proceedings of the Institution of Mechanical Engineers -- Part H -- Journal of Engineering in Medicine (Professional Engineering Publishing) Type: main |
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