A survey on fall detection: Principles and approaches

Authors:
Muhammad Mubashir;Ling Shao;Luke Seed
Affiliations:
Department of Electronic and Electrical Engineering, The University of Sheffield, UK;Department of Electronic and Electrical Engineering, The University of Sheffield, UK;Department of Electronic and Electrical Engineering, The University of Sheffield, UK
Venue:
Neurocomputing
Year:
2013

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Abstract

Fall detection is a major challenge in the public health care domain, especially for the elderly, and reliable surveillance is a necessity to mitigate the effects of falls. The technology and products related to fall detection have always been in high demand within the security and the health-care industries. An effective fall detection system is required to provide urgent support and to significantly reduce the medical care costs associated with falls. In this paper, we give a comprehensive survey of different systems for fall detection and their underlying algorithms. Fall detection approaches are divided into three main categories: wearable device based, ambience device based and vision based. These approaches are summarised and compared with each other and a conclusion is derived with some discussions on possible future work.