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New Advances and Challenges of Fall Detection Systems: A Survey

by Tao Xu 1, Yun Zhou 2,* and Jing Zhu 1
1
School of Software and Microelectronics, Northwestern Polytechnical University, 127 West Youyi Road, Xi’an 710072, Shaanxi, China
2
School of Education, Shaanxi Normal University, 199 South Chang’an Road, Xi’an 710062, Shaanxi, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2018, 8(3), 418; https://doi.org/10.3390/app8030418
Received: 31 January 2018 / Revised: 22 February 2018 / Accepted: 6 March 2018 / Published: 12 March 2018
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
Falling, as one of the main harm threats to the elderly, has drawn researchers’ attentions and has always been one of the most valuable research topics in the daily health-care for the elderly in last two decades. Before 2014, several researchers reviewed the development of fall detection, presented issues and challenges, and navigated the direction for the study in the future. With smart sensors and Internet of Things (IoT) developing rapidly, this field has made great progress. However, there is a lack of a review and discussion on novel sensors, technologies and algorithms introduced and employed from 2014, as well as the emerging challenges and new issues. To bridge this gap, we present an overview of fall detection research and discuss the core research questions on this topic. A total of 6830 related documents were collected and analyzed based on the key words. Among these documents, the twenty most influential and highly cited articles are selected and discussed profoundly from three perspectives: sensors, algorithms and performance. The findings would assist researchers in understanding current developments and barriers in the systems of fall detection. Although researchers achieve fruitful work and progress, this research domain still confronts challenges on theories and practice. In the near future, the new solutions based on advanced IoT will sustainably urge the development to prevent falling injuries.
Keywords: fall detection; survey; smart sensor; Internet of Things fall detection; survey; smart sensor; Internet of Things
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MDPI and ACS Style

Xu, T.; Zhou, Y.; Zhu, J. New Advances and Challenges of Fall Detection Systems: A Survey. Appl. Sci. 2018, 8, 418.

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