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EURASIP Journal on Advances in Signal Processing
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Nonlinear Analysis of the BOLD Signal

EURASIP Journal on Advances in Signal Processing volume 2009, Article number: 215409 (2009) Cite this article

Abstract

The linearized filtering approach to the hemodynamic system is limited in capturing the inherent nonlinearities of physiological systems. The nonlinear estimation method therefore should be thought of as a natural way to access the nonlinear data assimilation problem. In this paper, we present a nonlinear filtering algorithm which is computationally expensive compared to the existing linearization filtering algorithms, for hemodynamic data assimilation, to address the deficiencies inherent to linearization. Simultaneous estimation of the physiological states and the system parameters have been demonstrated in a simulated and real data. The method provides more reasonable inference about the parameters of models for hemodynamic data assimilation.

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Authors and Affiliations

  1. Department of Optical Engineering, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou, 310027, China

    Zhenghui Hu & Huafeng Liu

  2. Department of Radiology, Tongji Hospital of Tongji University, Shanghai, 200065, China

    Xiaohu Zhao

  3. B. Thomas Golisano College of Computing and Information Sciences, Rochester Institute of Technology, Rochester, NY, 14623, USA

    Zhenghui Hu & Pengcheng Shi

  4. University of Rochester Medical Center, Rochester, NY, 14642, USA

    Pengcheng Shi

Authors
  1. Zhenghui Hu
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  2. Xiaohu Zhao
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  3. Huafeng Liu
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  4. Pengcheng Shi
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Corresponding author

Correspondence to Pengcheng Shi.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Hu, Z., Zhao, X., Liu, H. et al. Nonlinear Analysis of the BOLD Signal. EURASIP J. Adv. Signal Process. 2009, 215409 (2009). https://doi.org/10.1155/2009/215409

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  • DOI: https://doi.org/10.1155/2009/215409

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