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    Bayesian Filter Design for Computational Medicine

    A State-Space Estimation Framework

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    Author(s)
    Wickramasuriya, Dilranjan S.
    Faghih, Rose T.
    Language
    English
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    Abstract
    This book serves as a tutorial that explains how different state estimators (Bayesian filters) can be built when all or part of the observations are binary. The book begins by briefly motivating the need for point process state estimation followed by an introduction to the overall approach, as well as some basic background material in statistics that are necessary for the equation derivations that are utilized in subsequent chapters. The subsequent chapters focus on different state-space models and provide step-by-step explanations on how to build the corresponding Bayesian filters. Each of the main chapters that describes a single state-space model also describes the corresponding MATLAB code examples at the end. Descriptions are also provided regarding the code. The code contains both simulated and experimental data examples. All the experimental data examples are taken from real-world experiments. The experiments involve the recording of skin conductance, heartrate and blood cortisol data. A MATLAB toolbox of code examples that cover the different filters covered in the book is included in a companion webpage. The book is primarily intended for graduate students in either electrical engineering or biomedical engineering who will be beginning research in state estimation related to point process data or mixed data (i.e., point processes and other types of observations). The book can also be used by practicing researchers who measure skin conductance and heart rate or pulsatile hormones in their own work (e.g. in psychology). This is an open access book.
    URI
    https://library.oapen.org/handle/20.500.12657/89933
    Keywords
    State-space estimation; Bayesian filtering; Bayesian decoder design; Physiological decoders; Mixed filters; Biomedical signal processing; Electrodermal activity analysis; skin response signal processing; Galvanic skin response signal; Galvanic skin response processing; Bayesian Filter Design neuroengineering; Bayesian Filter Design; computational medicine bayesian
    DOI
    10.1007/978-3-031-47104-9
    ISBN
    9783031471049, 9783031471032, 9783031471049
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Cham, 2024
    Grantor
    • New York University - [...]
    Imprint
    Springer International Publishing
    Classification
    Neurosciences
    Biomedical engineering
    Electronics engineering
    Digital signal processing (DSP)
    Biophysics
    Pages
    228
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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