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Enhancement of Energy Efficiency in Wireless Sensor Network with Mobile Sink: A Survey Read chapter Read first chapter

2023 | OriginalPaper | Chapter

A Comprehensive Study of Pose Estimation in Human Fall Detection

Authors : Shikha Rastogi, Jaspreet Singh

Published in: Proceedings of Third International Conference on Computing, Communications, and Cyber-Security

Publisher: Springer Nature Singapore

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Abstract

According to a study, unexpected fall is one of the main causes of sudden demise in elder persons. Therefore, it is very important to take immediate safety measures for the people having age 65 or above, or the people who are physically or mentally disabled. A powerful fall detection system to identify and provide immediate assistance to senior citizens or the people who is prone to falls is needed. A medical alert system with fall detection allows the user to summon assistance without pressing the call button. This review paper identifies the comparison in the approaches used for fall detection based on machine learning algorithm. A brief discussion on the methods used in pose estimation like OpenPose and PoseNet, which are majorly used to detect the fall and non-fall of a person is done. Moreover, we have also discussed the privacy concern of a person while using camera-based technique for detecting fall.

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Metadata
Title
A Comprehensive Study of Pose Estimation in Human Fall Detection
Authors
Shikha Rastogi
Jaspreet Singh
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Proceedings of Third International Conference on Computing, Communications, and Cyber-Security

Print ISBN: 978-981-19-1141-5

Electronic ISBN: 978-981-19-1142-2

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-19-1142-2_31