NDLI: Recognition of direction of fall by smartphone

Content Provider	IEEE Xplore Digital Library
Author	Ying-Wen Bai Shiao-Chian Wu Chia Hao Yu
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng., Fu Jen Catholic Univ., Taipei, Taiwan (Ying-Wen Bai; Shiao-Chian Wu; Chia Hao Yu)
Abstract	In this paper we enhance our fall monitor with our recognition of the direction of fall functionality. We not only analyze the change of acceleration but also analyze five typical actions of humans: walking, running, standing up, sitting down and jumping. Then we compare these actions with the acceleration characteristics of a fall: the weightlessness, the impact, and the overturning of the body. Because the waist is the center of gravity in the human body, our system is used more effectively when we place the smart phone at the waist. We also analyze the three different accelerations in space to infer the fall direction of the user. Our system is based both on an open source system platform and on the accelerometer in the smart phone.
Starting Page	1
Ending Page	6
File Size	1783110
Page Count	6
File Format	PDF
ISBN	9781479900312
ISSN	08407789
e-ISBN	9781479900336
e-ISBN	9781479900329
DOI	10.1109/CCECE.2013.6567781
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-05
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Acceleration Smart phones Accelerometers Temperature sensors Intelligent sensors Monitoring Fall direction Smart phone Accelerometer Fall detection
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

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