NDLI: Neural network evaluation for shoe insoles fitness

Content Provider	IEEE Xplore Digital Library
Author	Chung-Shing Wang Chung-Chuan Wang Teng-Ruey Chang
Copyright Year	2013
Description	Author affiliation: Dept. of Ind. Manage., Nan-Kai Univ. of Technol., Nan-Tou, Taiwan (Teng-Ruey Chang) \|\| Dept. of Multimedia & Game, Chung-Chou Univ., Chung-Hwa, Taiwan (Chung-Chuan Wang) \|\| Dept. of Ind. Design, Tung-Hai Univ., Taichung, Taiwan (Chung-Shing Wang)
Abstract	The purpose of this research is to evaluate and analyze the fitness for human foot in different shoe insoles. We find the most-related evaluation between foot shapes and shoe insoles by using the grey-relational approach. Based on the plantar pressure measurement on the shoe insoles, we put them into the artificial neural network (ANN) as the training pair (pressure-insole) for network training. After training iterations, the network will have enough generalizing capability to classify the pattern of the plantar pressure. Back-propagation neural network (BPNN) is used to convert and classify shoe insoles. By referring to the classified results estimated by the network, a designer can make the best decision for where the design project is heading. Furthermore, this approach can effectively reduce the design-cycle time and meet the customers' demands. Results and contributions in this paper are as follows. First of all, we conducted a foot experiment to verify research assumptions. Secondly, we investigated validity of using grey-relational approach to estimate the fitness of foot based on the plantar pressure data. Thirdly, we verified the validity of ANN's learning and classifying capabilities. Lastly, we used ANN to learn from the fitness data and predict the most appropriate insoles for the foot.
Sponsorship	IEEE Circuits Syst. Soc.
Starting Page	157
Ending Page	162
File Size	438108
Page Count	6
File Format	PDF
ISBN	9781467347143
ISSN	21579563
DOI	10.1109/ICNC.2013.6817962
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training grey-relational shoe insole plantar pressure Footwear Artificial neural networks Pressure measurement fitness evaluation Biological neural networks Foot back-propagation neural network
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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