Bayesian Filter Design for Computational Medicine: A State-Space Estimation Framework
暫譯: 計算醫學中的貝葉斯濾波器設計：一個狀態空間估計框架

Wickramasuriya, Dilranjan S., Faghih, Rose T.

Bayesian Filter Design for Computational Medicine: A State-Space Estimation Framework
  • 出版商: Springer
  • 出版日期: 2025-03-31
  • 售價: $1,950
  • 貴賓價: 9.5 折 $1,853
  • 語言: 英文
  • 頁數: 228
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3031471067
  • ISBN-13: 9783031471063
  • 相關分類: 機率統計學 Probability-and-statistics

    • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

這本書作為一個教程，解釋了當所有或部分觀測值為二元時，如何構建不同的狀態估計器（貝葉斯濾波器）。本書首先簡要說明了點過程狀態估計的必要性，接著介紹了整體方法，以及一些在後續章節中所需的統計學基本背景材料，以便進行方程推導。隨後的章節專注於不同的狀態空間模型，並提供逐步的解釋，說明如何構建相應的貝葉斯濾波器。

每個描述單一狀態空間模型的主要章節在結尾處也描述了相應的 MATLAB 代碼示例。代碼的描述也隨之提供。這些代碼包含模擬和實驗數據示例。所有的實驗數據示例均來自真實世界的實驗。這些實驗涉及皮膚電導、心率和血液皮質醇數據的記錄。一本包含本書中涵蓋的不同濾波器的 MATLAB 代碼示例工具箱也包含在一個伴隨的網頁中。

本書主要針對電機工程或生物醫學工程的研究生，這些學生將開始進行與點過程數據或混合數據（即點過程和其他類型的觀測）相關的狀態估計研究。本書也可供從事測量皮膚電導和心率或脈動激素的實踐研究者使用（例如在心理學領域）。

這是一本開放存取的書籍。

作者簡介

Dilranjan S. Wickramasuriya received his B.S. degree in electronic and telecommunication engineering from the University of Moratuwa, in 2014, and the M.S. degree in electrical engineering from the University of South Florida, in 2017. In 2020, he completed his Ph.D. degree in electrical engineering at the University of Houston. He works as a Software Engineer at hSenid Mobile Solutions.

Rose T. Faghih is an associate professor of Biomedical Engineering at the New York University (NYU) where she directs the Computational Medicine Laboratory. She received a bachelor's degree (summa cum laude) in Electrical Engineering (Honors Program Citation) from the University of Maryland, and S.M. and Ph.D. degrees in Electrical Engineering and Computer Science with a minor in Mathematics from Massachusetts Institute of Technology (MIT), where she was a member of the MIT Laboratory for Information and Decision Systems as well as the MIT-Harvard Neuroscience Statistics Research Laboratory. She completed her postdoctoral training at the Department of Brain and Cognitive Sciences and the Picower Institute for Learning and Memory at MIT as well as the Department of Anesthesia, Critical Care and Pain Medicine at the Massachusetts General Hospital. Dr. Faghih is the recipient of various awards including a 2023 National Institutes of Health (NIH) Maximizing Investigators' Research Award for Early Stage Investigators, a 2020 National Science Foundation CAREER Award, a 2020 MIT Technology Review Innovator Under 35 award, and a 2016 IEEE-USA New Face of Engineering award. In 2020, she was featured by the IEEE Women in Engineering Magazine as a "Woman to Watch". Moreover, she was selected by the National Academy of Engineering for the 2019 US and the 2023 EU-US Frontiers of Engineering Programs. Dr. Faghih is on the editorial board of PNAS Nexus by the National Academy of Sciences and IEEE Transactions on Neural Systems and Rehabilitation Engineering. Her research interests include wearable technologies, medical cyber-physical systems, neural and biomedical signal processing, as well as control, estimation, and system identification of biomedical and neural systems.

作者簡介(中文翻譯)

Dilranjan S. Wickramasuriya於2014年獲得摩拉圖瓦大學的電子與電信工程學士學位，並於2017年獲得南佛羅里達大學的電機工程碩士學位。2020年，他在休士頓大學完成電機工程博士學位。目前，他在hSenid Mobile Solutions擔任軟體工程師。

Rose T. Faghih是紐約大學（NYU）生物醫學工程的副教授，並負責計算醫學實驗室。她在馬里蘭大學獲得電機工程學士學位（summa cum laude，榮譽計畫獎），並在麻省理工學院（MIT）獲得電機工程和計算機科學碩士及博士學位，輔修數學。在MIT期間，她是MIT資訊與決策系統實驗室及MIT-哈佛神經科學統計研究實驗室的成員。她在MIT的腦與認知科學系及皮考爾學習與記憶研究所，以及麻省總醫院的麻醉、重症護理與疼痛醫學系完成了博士後訓練。Faghih博士獲得多項獎項，包括2023年國家衛生研究院（NIH）早期研究者最大化研究獎、2020年國家科學基金會CAREER獎、2020年MIT科技評論35歲以下創新者獎，以及2016年IEEE-USA工程新面孔獎。2020年，她被IEEE女性工程雜誌評選為「值得關注的女性」。此外，她還被美國國家工程院選為2019年美國及2023年歐盟-美國工程前沿計畫的成員。Faghih博士是國家科學院的PNAS Nexus及IEEE神經系統與康復工程期刊的編輯委員會成員。她的研究興趣包括可穿戴技術、醫療網路物理系統、神經與生物醫學信號處理，以及生物醫學和神經系統的控制、估計和系統識別。

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