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Patterns of Bipedal Walking on Tri-axial Acceleration Signals and Their Use in Identifying Falling Risk of Older People
Seoul, Korea September 20-September 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIT.2006.143Sixth IEEE International Conference o ...
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Jian Liu, Takehito Kanno, Masanori Akashi, Wenxi Chen, Daming Wei, Gengfeng Wu, Naotoshi Takeda, "Patterns of Bipedal Walking on Tri-axial Acceleration Signals and Their Use in Identifying Falling Risk of Older People," Computer and Information Technology, International Conference on, pp. 205, Sixth IEEE International Conference on Computer and Information Technology (CIT'06), 2006.
 
 
BibTex
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@article{ 10.1109/CIT.2006.143,
author = {Jian Liu and Takehito Kanno and Masanori Akashi and Wenxi Chen and Daming Wei and Gengfeng Wu and Naotoshi Takeda},
title = {Patterns of Bipedal Walking on Tri-axial Acceleration Signals and Their Use in Identifying Falling Risk of Older People},
journal ={Computer and Information Technology, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2687-X},
pages = {205},
doi = {http://doi.ieeecomputersociety.org/10.1109/CIT.2006.143},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer and Information Technology, International Conference on
TI - Patterns of Bipedal Walking on Tri-axial Acceleration Signals and Their Use in Identifying Falling Risk of Older People
SN - 0-7695-2687-X
SP
EP
A1 - Jian Liu,
A1 - Takehito Kanno,
A1 - Masanori Akashi,
A1 - Wenxi Chen,
A1 - Daming Wei,
A1 - Gengfeng Wu,
A1 - Naotoshi Takeda,
PY - 2006
KW - null
VL - 0
JA - Computer and Information Technology, International Conference on
ER -
 
Jian Liu, The University of Aizu, Japan
Takehito Kanno, The University of Aizu, Japan
Masanori Akashi, The University of Aizu, Japan
Wenxi Chen, The University of Aizu, Japan
Daming Wei, The University of Aizu, Japan
Gengfeng Wu, Shanghai University, China
Naotoshi Takeda, Takeda Clinic, Japan
Falls are the leading cause of injury-related death and hospitalization of aging people. To clarify this issue, temporal-spatial differences of gait between young people and the aging people with high falling risks are well investigated by many authors. Body acceleration is one of the measures receiving most interests, but major relevant literatures studied it only on one axis - mainly vertical direction. In this paper, we study the triaxial acceleration signals during body moving and find some patterns inside. Based on the patterns, we propose a method to identify walking waveforms within the signal of body acceleration, and derive some measurements for assessing the rhythmicity in walking. The experiments show that our measurements are effective in identifying aging people with walking problems.
Citation:
Jian Liu, Takehito Kanno, Masanori Akashi, Wenxi Chen, Daming Wei, Gengfeng Wu, Naotoshi Takeda, "Patterns of Bipedal Walking on Tri-axial Acceleration Signals and Their Use in Identifying Falling Risk of Older People," cit, pp.205, Sixth IEEE International Conference on Computer and Information Technology (CIT'06), 2006
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