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Second Heart Sound (S2) Decomposition by Hilbert Vibration Decomposition (HVD) for Affective Signal Modeling and Learning

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Part of the book series:Lecture Notes in Computer Science ((LNISA,volume 8390))

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Abstract

This article presents a novel signal decomposition method, Hilbert vibration decomposition (HVD), for analyzing one of the major heart sound components second heart sound (S2) signal for affective signal modeling. In this proposed method, three kinds of simulated S2 signals are generated and the typical one is chosen for decomposition. For HVD method, a FIR filter is designed to separate each of the decomposed components. Finally, performance indicators, including the number of decomposed components, Hilbert spectrum, and spectral centroids, are measured.

To evaluate the performance of HVD, the decomposed components are compared with those generated by empirical mode decomposition (EMD) method. The experimental result shows that the number of meaningful decomposed components and frequency resolutions by using HVD method are better than those by using EMD. Such results also reveal the HVD method is superior to the normal EMD method, especially for low frequency narrow band bio-signals such second heart sound, thereby facilitating generating discriminant features for model learning.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan

    Shovan Barma, Bo-Wei Chen, Hung-Ming Wang, Hung-Jui Wang & Jhing-Fa Wang

  2. Department of Digital Multimedia Design, Tajen University, Yanpu Township, Pingtung County, Taiwan

    Jhing-Fa Wang

Authors
  1. Shovan Barma

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  2. Bo-Wei Chen

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  3. Hung-Ming Wang

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  4. Hung-Jui Wang

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  5. Jhing-Fa Wang

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Corresponding author

Correspondence toShovan Barma.

Editor information

Editors and Affiliations

  1. Dickson Computer Systems, Kowloon, Hong Kong SAR

    Dickson K. W. Chiu

  2. The University of Hong Kong, Pokfulam, Hong Kong SAR

    Minhong Wang

  3. University of Craiova, Craiova, Romania

    Elvira Popescu

  4. City University of Hong Kong, Hong Kong, Hong Kong SAR

    Qing Li

  5. City University of Hong Kong, Kowloon, Hong Kong SAR

    Rynson Lau

  6. Department of Computer Science and Information Engineering, National Central University, Jhongli City, Taiwan

    Timothy K. Shih

  7. Department of Electrical Engineering, National Cheng Kung University, Taiwan, Taiwan

    Chu-Sing Yang

  8. Digital Systems Centre for Research & Technology Hellas (CERTH), University of Piraeus Dept of Digital Systems, Piraeus, Greece

    Demetrios G. Sampson

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© 2015 Springer-Verlag Berlin Heidelberg

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Barma, S., Chen, BW., Wang, HM., Wang, HJ., Wang, JF. (2015). Second Heart Sound (S2) Decomposition by Hilbert Vibration Decomposition (HVD) for Affective Signal Modeling and Learning. In: Chiu, D.,et al. Advances in Web-Based Learning – ICWL 2013 Workshops. ICWL 2013. Lecture Notes in Computer Science(), vol 8390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46315-4_23

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