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The development of Artificial Neural Networks (ANN) for falls detection

Author(s)
Yodpijit, Nantakrit
Sittiwanchai, Teppakorn
Jongprasithporn, Manutchanok
Date Issued
June 7, 2017
Type
Conference Paper
DOI
10.1109/ICCAR.2017.7942757
Abstract
This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for detecting body orientation and movement. The Threshold Based and Artificial Neural Networks (ANN) algorithm were developed to differentiate between Activities of Daily Living (ADL). Results indicated the possibility of using the new threshold-based method with ANN algorithm to reduce the number of false positive (false alarm) outcomes and improve the accuracy of fall detection system.
Citation
2017 3rd International Conference on Control Automation and Robotics Iccar 2017, 547-550, 2017
Subjects

Aging

Algorithm

Artificial neural net...

Fall detection system...

Motion sensors

Threshold

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