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Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
Possible Life Saver: A Review on Human Fall Detection Technology
Robotics (Basel), v 9(3)
01 Sep 2020
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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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Details
- Title
- Possible Life Saver: A Review on Human Fall Detection Technology
- Creators
- Zhuo Wang - Drexel Univ, Dept Elect & Comp Engn, Philadelphia, PA 19131 USAVignesh Ramamoorthy - Drexel Univ, Dept Elect & Comp Engn, Philadelphia, PA 19131 USAUdi Gal - GraceFall Inc, Penn Valley, PA 19072 USAAllon Guez - Drexel University
- Publication Details
- Robotics (Basel), v 9(3)
- Publisher
- Mdpi
- Number of pages
- 19
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000578163100001
- Scopus ID
- 2-s2.0-85089687030
- Other Identifier
- 991019169520004721
UN Sustainable Development Goals (SDGs)
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Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Robotics