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Possible Life Saver: A Review on Human Fall Detection Technology
Journal article   Open access   Peer reviewed

Possible Life Saver: A Review on Human Fall Detection Technology

Zhuo Wang, Vignesh Ramamoorthy, Udi Gal and Allon Guez
Robotics (Basel), v 9(3)
01 Sep 2020
DOI: https://doi.org/10.3390/robotics9030055
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.3390/robotics9030055View
Published, Version of Record (VoR)CC BY V4.0,  Open

Abstract

Robotics Science & Technology Technology
Among humans, falls are a serious health problem causing severe injuries and even death for the elderly population. Besides, falls are also a major safety threat to bikers, skiers, construction workers, and others. Fortunately, with the advancements of technologies, the number of proposed fall detection systems and devices has increased dramatically and some of them are already in the market. Fall detection devices/systems can be categorized based on their architectures as wearable devices, ambient systems, image processing-based systems, and hybrid systems, which employ a combination of two or more of these methodologies. In this review paper, a comparison is made among these major fall detection systems, devices, and algorithms in terms of their proposed approaches and measure of performance. Issues with the current systems such as lack of portability and reliability are presented as well. Development trends such as the use of smartphones, machine learning, and EEG are recognized. Challenges with privacy issues, limited real fall data, and ergonomic design deficiency are also discussed.

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27 Record Views
48 citations in Web of Science
63 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Web of Science research areas
Robotics
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