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A Handbook of Internet of Things in Biomedical and Cyber Physical SystemA SVM Algorithm for Falling Detection in an IoTs-Based System

A Handbook of Internet of Things in Biomedical and Cyber Physical System: A SVM Algorithm for... [Falling of elderly people is one of main reasons causing serious injuries or the risk of early death. However, this may be reduced by using an IoTs-based fall detection system, in which a SVM algorithm and PCA features are applied. In addition, datasets collected from tri-axial accelerometer sensors and/or Kinect camera systems are transferred to a central Hub via Zigbee interface and are updated continuously to a cloud server for processing and detecting fall states. In addition, fall messages can be sent to relatives through smartphones and/or healthcare centers for alert and supporting soon. Experimental results show to illustrate the effectiveness of the proposed system.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Handbook of Internet of Things in Biomedical and Cyber Physical SystemA SVM Algorithm for Falling Detection in an IoTs-Based System

Part of the Intelligent Systems Reference Library Book Series (volume 165)
Editors: Balas, Valentina E.; Solanki, Vijender Kumar; Kumar, Raghvendra; Ahad, Md. Atiqur Rahman
Nguyen, Thanh-Hai; Nguyen, Thanh-Tam; Ngo, Ba-Viet
A Handbook of Internet of Things in Biomedical and Cyber Physical System — Jul 17, 2019
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References (39)

Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2020
ISBN
978-3-030-23982-4
Pages
139 –170
DOI
10.1007/978-3-030-23983-1_6
Publisher site
See Chapter on Publisher Site

Abstract

[Falling of elderly people is one of main reasons causing serious injuries or the risk of early death. However, this may be reduced by using an IoTs-based fall detection system, in which a SVM algorithm and PCA features are applied. In addition, datasets collected from tri-axial accelerometer sensors and/or Kinect camera systems are transferred to a central Hub via Zigbee interface and are updated continuously to a cloud server for processing and detecting fall states. In addition, fall messages can be sent to relatives through smartphones and/or healthcare centers for alert and supporting soon. Experimental results show to illustrate the effectiveness of the proposed system.]

Published: Jul 17, 2019

Keywords: IoTs-based system; Accelerometer sensor; Kinect camera; SVM algorithm; Falling detection; Hub via ZigBee interface

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