Bayesian Filter Design for Computational Medicine: A State-Space Estimation Framework

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: 2024-03-30
  • 售價: $2,560
  • 貴賓價: 9.5 折 $2,432
  • 語言: 英文
  • 頁數: 228
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031471032
  • ISBN-13: 9783031471032
  • 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, heart rate 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)

本書作為一本教程，解釋了當所有或部分觀測值為二進制時，如何構建不同的狀態估計器（貝葉斯濾波器）。書籍首先簡要介紹了點過程狀態估計的需求，然後介紹了整體方法以及在後續章節中使用的方程推導所需的一些基本統計背景知識。接下來的章節專注於不同的狀態空間模型，並提供了逐步解釋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還在末尾描述了相應的MATLAB代碼示例。代碼的描述也提供了相關說明。代碼包含了模擬和實驗數據示例。所有的實驗數據示例都來自於真實世界的實驗。附帶網頁中包含了一個MATLAB代碼示例的工具箱，涵蓋了書中介紹的不同濾波器。

本書主要面向電氣工程或生物醫學工程的研究生，他們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。本書也可供實踐研究人員使用，他們在自己的工作中測量皮膚電導、心率或脈動激素（例如心理學領域）。

本書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年獲得斯里蘭卡莫拉圖瓦大學的電子與通訊工程學士學位，並於2017年獲得美國南佛羅里達大學的電機工程碩士學位。2020年，他在休斯頓大學完成了電機工程博士學位。他目前在hSenid Mobile Solutions擔任軟體工程師。

Rose T. Faghih是紐約大學生物醫學工程的副教授，並負責指導計算醫學實驗室。她在馬里蘭大學獲得了電機工程學士學位（榮譽課程），並在麻省理工學院獲得了電機工程和計算機科學的碩士和博士學位，並在其中擔任了麻省理工學院信息和決策系統實驗室以及麻省理工學院-哈佛大學神經科學統計研究實驗室的成員。她在麻省理工學院的大腦和認知科學系以及麻省綜合醫院的麻醉、重症護理和疼痛醫學系完成了博士後培訓。Faghih博士獲得了多個獎項，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 Technology Review 35歲以下創新者獎和2016年IEEE-USA新工程師獎。2020年，她被IEEE Women in Engineering Magazine選為“值得關注的女性”。此外，她還被美國國家工程院選為2019年美國和2023年歐盟-美國工程前沿計劃的成員。Faghih博士是國家科學院的PNAS Nexus和IEEE Transactions on Neural Systems and Rehabilitation Engineering的編輯委員會成員。她的研究興趣包括可穿戴技術、醫療物理系統、神經和生物醫學信號處理，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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