A survey on fall detection: Principles and approaches

Muhammad Mubashir, Ling Shao, Luke Seed

Research output: Contribution to journalArticlepeer-review

542 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)144-152
JournalNeurocomputing
Volume100
DOIs
Publication statusPublished - 16 Jan 2013

Fingerprint

Dive into the research topics of 'A survey on fall detection: Principles and approaches'. Together they form a unique fingerprint.

Cite this