A Panoramic Study of Fall Detection Technologies
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Authors
Almazaydeh, Laiali
Al-Otoon, Khitam
Al-Dmour, Ayman
Elleithy, Khaled M.
Issue Date
2016-05
Type
Article
Language
en_US
Keywords
Fall detection , Elderly monitoring , Accelerometer , Tilt , Gyroscope , Vision-based , Ambience-base , Pressure sensor , Support vector machine , k-nearest neighbors algorithm , Classification
Alternative Title
Abstract
Falls are a major risk of injury for elderly aged 65 or over, blind people, people with balance disorder and leg weakness. In this regard, assistive technology which aims to identify fall events at real time can reduce the rate of impairments and mortality. This study offer a literature research reference value for bioengineers for further research. Much of the past and the current fall detection research, the vital signals features and the way features are extracted and fed to a classifier are introduced. The study concludes with an assessment of the current technologies highlighting their critical limitations along with suggestions for future research direction in this rapidly developing field of study.
Description
Citation
Publisher
International Journal of Computer Science Issues