Volume 8 Number 1 (Jan. 2018)
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IJBBB 2018 Vol.8(1): 20-31 ISSN: 2010-3638
doi: 10.17706/ijbbb.2018.8.1.20-31

Visual Data Analysis Methods Using OpenCV Programs to Evaluate Walking and Falling with a Japanese Walking Support System

Shinji Kawakura
Abstract—In recent years, researchers and engineers have come together to develop diverse, applied, and practical sensing systems to solve the difficulties faced in the development of advanced support systems, technical teaching, and safety issues for physically challenged and elderly people. Following a sequence of studies developing promising systems that address a number of nursing challenges, the purpose of this prospective research was to develop effective systems and demonstrate their accuracy and utility for the aforementioned people. In this kinematic investigation, we develop a physical analysis system, which uses two video cameras to obtain visual data of physically challenged and elderly people from two directions (the subject’s front and left). These systems use the OpenCV 2.4.9 package, including the library and header files, and programs originally written in Visual C++. This study examines the qualitative and quantitative characteristics and the unique parameters of (1) the main shaft (the principal axis of inertia) of the subject and the walking support system to highlight the differences between two frames using binary video data, and (2) coordinate values of characteristic points that are set automatically. Finally, we present the output values for the physical measurements obtained from various viewpoints. In future, these methods could be of practical use in providing alternative directions for developers and care managers to assess and treat users’ conditions in both outdoor (e.g., playgrounds for the elderly) and indoor settings (e.g., hospitals).

Index Terms—Falling with patients and the elderly, human engineering methodology, OpenCV, safe technology measurement, walking support system.

The author is with National Institute of Advanced Industrial Science and Technology (AIST), Department of Information Technology and Human Factors, Robot Innovation Research Center 1-1-1 Umezono, Tsukuba, Ibaraki 305-8560 Japan (email: s.kawakura@aist.go.jp).

Cite: Shinji Kawakura, "Visual Data Analysis Methods Using OpenCV Programs to Evaluate Walking and Falling with a Japanese Walking Support System," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 8, no. 1, pp. 20-31, 2018.

General Information

ISSN: 2010-3638
Frequency: Bimonthly (2011-2015); Quarterly (Since 2016)
DOI: 10.17706/IJBBB
Editor-in-Chief: Prof. Ebtisam Heikal 
Abstracting/ Indexing: Electronic Journals Library, Chemical Abstracts Services (CAS), Engineering & Technology Digital Library, Google Scholar, and ProQuest.
E-mail: ijbbb@iap.org
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