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A Handbook of Internet of Things in Biomedical and Cyber Physical System

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Cover of 'A Handbook of Internet of Things in Biomedical and Cyber Physical System'

Table of Contents

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    Book Overview
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    Chapter 1 The Basics of Healthcare IoT: Data Acquisition, Medical Devices, Instrumentations and Measurements
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    Chapter 2 Hardware Based Cyber System Using High Performance Crypto Hash Bloom Filter for Network Security and Privacy Preserving Applications
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    Chapter 3 Security Analysis and a Potential Layer to Layer Security Solution of Medical Cyber-Physical Systems
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    Chapter 4 The Internet of Things and Its Applications in Cyber Security
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    Chapter 5 Security Challenges for Designing Wearable and IoT Solutions
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    Chapter 6 A SVM Algorithm for Falling Detection in an IoTs-Based System
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    Chapter 7 Transforming Healthcare Through Various Technique in Internet of Things
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    Chapter 8 Closeness Factor Based Clustering Algorithm (CFBA) and Allied Implementations—Proposed IoMT Perspective
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    Chapter 9 A Deep Learning Framework for Heart Disease Classification in an IoTs-Based System
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    Chapter 10 Wearable Devices and IoT
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    Chapter 11 IoT Sensor Data Integration in Healthcare using Semantics and Machine Learning Approaches
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    Chapter 12 Challenges and Opportunities of Internet of Things for Health Care
Attention for Chapter 6: A SVM Algorithm for Falling Detection in an IoTs-Based System
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Citations

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Chapter title
A SVM Algorithm for Falling Detection in an IoTs-Based System
Chapter number 6
Book title
A Handbook of Internet of Things in Biomedical and Cyber Physical System
Published by
Springer, Cham, January 2020
DOI 10.1007/978-3-030-23983-1_6
Book ISBNs
978-3-03-023982-4, 978-3-03-023983-1
Authors

Thanh-Hai Nguyen, Thanh-Tam Nguyen, Ba-Viet Ngo, Nguyen, Thanh-Hai, Nguyen, Thanh-Tam, Ngo, Ba-Viet

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 20%
Unspecified 1 10%
Lecturer 1 10%
Student > Doctoral Student 1 10%
Student > Master 1 10%
Other 1 10%
Unknown 3 30%
Readers by discipline Count As %
Unspecified 1 10%
Business, Management and Accounting 1 10%
Computer Science 1 10%
Medicine and Dentistry 1 10%
Unknown 6 60%

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