DocumentCode :
2475089
Title :
How much information could be revealed by analyzing data from pressure sensors attached to shoe insole?
Author :
Chakraborty, Goutam ; Dendou, Tetsuhiro ; Kikuchi, Daigo ; Chiba, Kazuya
Author_Institution :
Fac. of Software & Inf. Sc., Iwate Prefectural Univ., Iwate, Japan
fYear :
2012
fDate :
13-16 May 2012
Firstpage :
1963
Lastpage :
1967
Abstract :
Data collected from pressure sensors attached to shoe insole is a rich source of information. (1) We can detect faults in walking and balancing problems for old people. (2) The pressure sensor data can be used to design personalized foot orthoses. (3) We can calculate the calorie burnt, even when walking and jogging are mixed, and the road slope changes. (4) We can use the data to train sprinters or tennis players. (5) We can even use the data for person identification. In addition, it can be used for alarms for situations arising from mis-handling of machines, like accelerator pedal in a car. We attached very thin pressure sensors on top of a shoe insole and collected data. A few important and readily detectable features from the time series data collected by those sensors are extracted and used for person identification, or to classify whether a person is walking or jogging. Nearly 100% classification accuracy was achieved. Thus, the target to classify whether the person is walking or jogging or climbing up or down the stairs is possible. This success also encouraged us to investigate whether it is possible to find the body weight and the step-length from this data. Once that is possible, the system can accurately deliver the calorie burnt at the end of the day. We will further explore the possibility, using sophisticated feature extraction and classification techniques, to detect faults in walking and predict the probability of fall for elderly people, or people with problem in balancing due to various diseases or caused by accidents.
Keywords :
data analysis; fault diagnosis; feature extraction; footwear; pressure sensors; probability; time series; body weight; calorie burnt calculation; car accelerator pedal; classification technique; data analysis; fault detection; feature detection extraction; machine mishandling; person data identification; personalized foot orthoses design; pressure sensor; probability prediction; road slope change; shoe insole; step-length; time series data collection; Hardware; Nickel; Senior citizens;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International
Conference_Location :
Graz
ISSN :
1091-5281
Print_ISBN :
978-1-4577-1773-4
Type :
conf
DOI :
10.1109/I2MTC.2012.6229115
Filename :
6229115
Link To Document :
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