DEVELOPMENT OF WEARABLE HUMAN FALL DETECTION SYSTEM USING MULTILAYER PERCEPTRON NEURAL NETWORK

This paper presents an accurate wearable fall detection system which can identify the occurrence of falls among elderly population. A waist worn tri-axial accelerometer was used to capture the movement signals of human body. A set of laboratory-based falls and activities of daily living (ADL) were p...

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Hlavní autoři:	Hamideh Kerdegari, Khairulmizam Samsudin, Abdul Rahman Ramli, Saeid Mokaram
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Springer 2013-02-01
Edice:	International Journal of Computational Intelligence Systems
Témata:	Wearable fall detection system Tri-axial accelerometer Classification Multilayer perceptron
On-line přístup:	https://www.atlantis-press.com/article/25868374.pdf
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