대한인간공학회지 (Journal of the Ergonomics Society of Korea)

  • 제36권5호
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  • Pages.395-409
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  • 2017
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  • 1229-1684(pISSN)
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  • 2093-8462(eISSN)
대한인간공학회 (Ergonomics Society of Korea)
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The Optimization of the Number and Positions of Foot Pressure Sensors to Develop Smart Shoes

  • Yoo, Sihyun (Motion Innovation Center, Korea National Sport University) ;
  • Gil, Hojong (Motion Innovation Center, Korea National Sport University) ;
  • Kim, Jongbin (Motion Innovation Center, Korea National Sport University) ;
  • Ryu, Jiseon (Motion Innovation Center, Korea National Sport University) ;
  • Yoon, Sukhoon (Motion Innovation Center, Korea National Sport University) ;
  • Park, Sang Kyoon (Motion Innovation Center, Korea National Sport University)
  • 투고 : 2017.04.06
  • 심사 : 2017.07.27
  • 발행 : 2017.10.31
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초록

Objective: The purpose of this study was to optimize the number and positions of foot pressure sensors using the reliability analysis of the center of pressure (COP) in smart shoes. Background: Foot pressure can be different according to foot region, and it is important which region of the foot pressure needs to be measured. Method: Thirty adults (age: $20.5{\pm}1.8years$, body weight: $71.4{\pm}6.5kg$, height: $1.76{\pm}0.04m$) participated in this study. The foot pressure data were collected using the insole of Pedar-X system (Novel GmbH, USA) with a sampling frequency of 100Hz during 1.3m/s speed walking on the treadmill (Instrumented treadmill, Bertec, USA). The intraclass correlation coefficients (ICC) were calculated between the COP positions using 4, 5, 6, 7, 8, and 99 sensors, while one-way repeated measure ANOVA was performed between the standard deviation (SD) of the COP positions. Results: The medio-lateral (M/L) COP position using 99 sensors was positively correlated with the M/L COP positions using 6, 7, and 8 sensors; however, it was not correlated with the M/L COP positions using 4 and 5 sensors during landing phase (1~4%) (p<.05). The antero-posterior (A/P) COP position using 99 sensors was positively correlated with the A/P COP positions using 4, 5, 6, 7, and 8 sensors (p<.05). The SD of the COP position using 99 sensors was smaller than the SD of the M/L COP positions using 4, 5, 6, 7, and 8 sensors (p<.05). Conclusion: Based on our findings, it is desirable to arrange at least 6 sensors in smart shoes. Application: The study of optimizing the number and positions of foot pressure sensors would contribute to developing more effective smart shoes using foot pressure technology.

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참고문헌

  1. Bamberg, S., Benbasat, A.Y., Scarborough, D.M., Krebs, D.E. and Paradiso, J.A., Gait analysis using a shoe-integrated wireless sensor system. IEEE Transactions on Information Technology in Biomedicine, 12(4), 413-423, 2008. https://doi.org/10.1109/TITB.2007.899493
  2. Davis, T.K., The foot length to stature ratio: A study of racial variance. Master thesis of Texas Tech University, 1990.
  3. Dogan, A., Uslu, M., Aydinlioglu, A., Harman, M. and Akpinar, F., Morphometric study of the human metatarsals and phalanges. Clinical Anatomy, 20, 209-214, 2007. https://doi.org/10.1002/ca.20348
  4. Doke, J., Donelan, J.M. and Kuo, A.D., Mechanics and energetics of swinging the human leg. The Journal of Experimental Biology, 208, 439-445, 2004.
  5. Hessert, M.J., Vyas, M., Leach, J., Hu, K., Lipsitz, L.A. and Novak, V., Foot pressure distribution during walking in young and old adults. BMC Geriatrics, 5(8), 2005.
  6. Isman, R.E. and Isman, V.T., Anthropometric studies of the human foot and ankle. Bulletin of Prosthetics Research, 97-129, 1969.
  7. Lee, S.I., Park, E., Huang, A., Mortazavi, B., Garst, J.H., Jahanforouz, N., Espinal, M., Siero, T., Pollack, S., Afridi, M., Daneshvar, M., Ghias, S., Lu, D.C. and Sarrafzadeh, M., Objectively quantifying walking ability in degenerative spinal disorder patients using sensor equipped smart shoes. Medical Engineering and Physics, 19(25), 1-8, 2016.
  8. Pappas, I.P.I., Keller, T., Mangold, S., Popovic, M.R., Dietz, V. and Morari, M., A reliable gyroscope-based gait-phase detection sensor embedded in a shoe insole. IEEE Sensors Journal, 4(2), 268-274, 2004. https://doi.org/10.1109/JSEN.2004.823671
  9. Park, S.B., Lee, K.D., Kim, D.W., Yoo, J.W., Kim, K.H., Jun, S.P., Ryu, W.H., Kim, J.H., Choi, M.J. and Jun, J.W., Development of smart shoes with indivisual personalized mobile health management system. Proceedings of the Conference of Ergonomics Society of Korea, 11, 141-144, 2014.
  10. Pietak, A., Ma, S., Beck, C.W. and Stringer, M.D., Fundamental ratios and logarithmic periodicity in human limb bones. Journal of Anatomy, 222, 526-537, 2013. https://doi.org/10.1111/joa.12041
  11. Razak, A.H.A., Zayegh, A., Begg, R.K. and Wahab, Y., Foot Plantar Pressure Measurement System: A Review. Sensors, 12, 9884-9912, 2012. https://doi.org/10.3390/s120709884
  12. Scott, S.H. and Winter, D.A., Internal forces at chronic running injury sites. Medicine and Scinece in Sports and Exercise, 22(3), 357-369, 1990.
  13. Seo, D.H. and Jang, S.W., Design and implementation of a smart shoes module based on arduino. Journal of the Korea Institute of Information and Communication Engineering, 19(11), 2697-2702, 2015. https://doi.org/10.6109/jkiice.2015.19.11.2697
  14. Shim, S., Jeon, S., Lee, C., Han, Y., Lee, G., Lee, E. and Jung, I., Smart shoes based on internet of things. Proceedings of the Conference of Korean Institute of Information Scientists and Engineers, 12, 449-451, 2015.
  15. Shu, L., Hua, T., Wang, Y., Li, Q. and Feng, D.D., In-Shoe Plantar Pressure Measurement and Analysis System Based on Fabric Pressure Sensing Array. IEEE Transactions on Information Technology In Biomedicine, 14(3), 767-775, 2010. https://doi.org/10.1109/TITB.2009.2038904
  16. Stewart, A., Casey, M., Laura, F., Patricia, M., Edward, P., James, A. and Joseph, H., The Impact of Footwear and Packweight on Injury and Illness Among Long-Distance Hikers. Wilderness and Environmental Medicine, 20, 250-256, 2009. https://doi.org/10.1580/08-WEME-OR-196R2.1
  17. Tirosh, O. and Sparrow, W.A., Age and walking speed effects on muscle recruitment in gait termination. Gait and Posture, 21, 279-288, 2005. https://doi.org/10.1016/j.gaitpost.2004.03.002
  18. Whittle, M.W., Gait Analysis: Introduction. Oxford Orthopaedic Engineering Centre: University of Oxford, 1990.
  19. Yoo, S.H., Kim, J.B., Ryu, J.S., Yoon, S.H. and Park, S.K., Comparative analysis of gait parameters and symmetry between preferred walking speed and walking speed by using the froude number. Korean Journal of Sport Biomechanics, 26(2), 221-228, 2016. https://doi.org/10.5103/KJSB.2016.26.2.221