Top > JRM > A System for Predicting Unprecedented Injury by Spatiotemporal ...

single-rb.php

JRM Vol.24 No.5 pp. 838-850
doi: 10.20965/jrm.2012.p0838
(2012)

Paper:

Views over last 60 days: 663

A System for Predicting Unprecedented Injury by Spatiotemporally Superimposing Children’s Normal Behavior

Yoshinori Koizumi*1,*2,*3, Yoshifumi Nishida*2, Koji Kitamura*2,
Yusuke Miyazaki*4, Yoichi Motomura*2, and Hiroshi Mizoguchi*1,*2

*1Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan

*2National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan

*3Research Fellow of the Japan Society for the Promotion of Science

*4Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8552, Japan

Received:
February 29, 2012
Accepted:
July 12, 2012
Published:
October 20, 2012
Creative Commons License
Keywords:
injury prediction, injury prevention, risk assessment, human activity observation, impact biomechanics
Abstract
Predicting injuries in daily life is important in the field of product safety design and risk assessment. However, in the case of children, it is usually thought that unprecedented injuries are difficult to predict because they are caused by “irregular” child behavior. Despite the prevalence of this belief, this study proposes a new injury prediction system based on the view that unprecedented injuries can, in fact, be predicted by identifying high-risk combinations of “normal” behaviors and environmental states. In this article, we also propose an injury prediction system based on spatiotemporally superimposing normal child behavior. The proposed system enables us to consistently predict injury processes consisting of the situation leading to the injury, the impact occurrence, and the resulting injury. This paper also presents an example of a system application for predicting potential injuries around a swing set in an actual park. To prove the effectiveness of the proposed system, we compare the patterns of accident processes predicted by the system with those of actual incident processes found in our observations of normal behaviors.
Cite this article as:
Y. Koizumi, Y. Nishida, K. Kitamura, Y. Miyazaki, Y. Motomura, and H. Mizoguchi, “A System for Predicting Unprecedented Injury by Spatiotemporally Superimposing Children’s Normal Behavior,” J. Robot. Mechatron., Vol.24 No.5, pp. 838-850, 2012.
Data files:
References
  1. [1] World Health Organization (WHO), “World report on child injury prevention,” M. Peden, K. Oyegbite, J. Ozanne-Smith, A. A. Hyder, C. Branche, A. F. Rahman, F. Rivara, and K. Bartolomeos (Eds.), 2008.
  2. [2] ISO/ICE, Guide 51 Safety Aspects – Guidelines for Their Inclusion in Standards, 1999.
  3. [3] ISO/IEC, Guide 50 Safety Aspects – Guidelines for child safety, 2002.
  4. [4] P. Berchialla, A. Stancu, C. Scarinzi, S. Snidero, R. Corradetti, and D. Gregori, “Web-based tool for injury risk assessment of foreign body injuries in children,” J. of Biomedical Informatics, Vol.41, No.4, pp. 544-556, 2008.
  5. [5] D. Stool, G. Rider, and J. R. Welling, “Human factors project: Development of computer models of anatomy as an aid to risk management,” Int. J. of Pediatric Otorhinolaryngology, Vol.43, No.3, pp. 217-227, 1998.
  6. [6] Y. Inomata, N. Iwai, Y. Maeda, S. Kobayashi, O. Hiroyuki, and N. Takahashi, “Development of the pop-up engine hood for pedestrian head protection,” The 21st ESV Conf. Proc., Paper Number 09-0067, 2009.
  7. [7] J. J. Gibson, “The Senses Considered As Perceptual Systems,” Houghton Mifflin, 1966.
  8. [8] P. Martin and P. Bateson, “Measuring Behaviour an introductory guide,” Cambridge University Press, 1986.
  9. [9] Y. Miyazaki, Y. Murai, Y. Nishida, T. Yamanaka, M. Mochimaru, and M. Kouchi, “Head Injury Analysis In Case of Fall from Playground Equipment Using Child Fall Simulator,” The impact of Technology on Sport, Vol.3, pp. 417-421, 2009.
  10. [10] Y. Nishida, Y. Motomura, K. Kitamura, and T. Yamanaka, “Representation and Statistical Analysis of Childhood Injury by Bodygraphic Information System,” Proc. of The 10th Int. Conf. on Geo-Computation, pp. 194-202, 2009.
  11. [11] T. Ishikawa, K. Kitamura, Y. Sugimoto, Y. Nishida, Y. Motomura, T. Yamanaka, and H. Mizoguchi, “Cost analysis of playground equipment injury at school using large-scale school insurance data of Japan,” Injury Prevention (Proc. of the 10th world Conf. on injury prevention and safety promotion), Vol.16, Suppl. 1, p. A234, 2010.
  12. [12] Supporting Online Materials:[a] Ministry of Health, Labour and Welfare, “Trends in leading causes of death: Japan,” Vital statistics of Japan 2009.
    http://www.e-stat.go.jp/SG1/estat/ListE.do?lid=000001066473 (Accessed May 18, 2011)
  13. [13] [b] Research Institute of Human Engineering for Quality Life, “Children’s Anthropometric Database (Website in Japanese).”
    http://www.hql.jp/database/children/ (Accessed Jan. 17, 2011)

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

Copyright© 2012 by Fuji Technology Press Ltd. and Japan Society of Mechanical Engineers. All right reserved.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 22, 2024