Physical Therapy Rehabilitation Science

  • 제11권3호
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  • Pages.311-320
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  • 2022
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  • 2287-7576(pISSN)
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  • 2287-7584(eISSN)
물리치료재활과학회 (korean Academy of Physical Therapy Rehabilitation Science)
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Reliability and Validity Study of Inertial Sensor-Based Application for Static Balance Measurement

  • Park, Young Jae (Division of Rehabilitation unit, Department of Rehabilitation Medicine, Kangbuk Samsung Hospital) ;
  • Jang, Ho Young (Department of Physical Therapy, Catholic University Eunpyeong St. Mary's Hospital) ;
  • Kim, Kwon Hoi (Department of Physical Therapy, Catholic University Uijeongbu St. Mary's Hosipital) ;
  • Hwang, Dong Ki (Department of Physical Therapy, Graduate School of Sahmyook University) ;
  • Lee, Suk Min (Department of Physical Therapy, Graduate School of Sahmyook University)
  • 투고 : 2022.06.19
  • 심사 : 2022.09.16
  • 발행 : 2022.09.30
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초록

Objective: To investigate the reliability and validity of static balance measurements using an acceleration sensor and a gyroscope sensor in smart phone inertial sensors. Design: Equivalent control group pretest-posttest. Methods: Subjects were forty five healthy adults aged twenty to fifty-years-old who had no disease that could affect the experiment. After pre-test, all participants wore a waist band with smart phone, and conducted six static balance measurements on the force plate twice for 35 seconds each. To investigate the test-retest reliability of both smart phone inertial sensors, we compared the intra-correlation coefficient (ICC 3, 1) between primary and secondary measurements with the calculated root mean scale-total data. To determine the validity of the two sensors, it was measured simultaneously with force plate, and the comparision was done by Pearson's correlation. Results: The test-retest reliability showed excellent correlation for acceleration sensor, and it also showed excellent to good correlation for gyroscope sensor(p<0.05). The concurrent validity of smartphone inertial sensors showed a mostly poor to fair correlation for tandem-stance and one-leg-stance (p<0.05) and unacceptable correlation for the other postures (p>0.05). The gyroscope sensor showed a fair correlation for most of the RMS-Total data, and the other data also showed poor to fair correlation (p<0.05). Conclusions: The result indicates that both acceleration sensor and gyroscope sensor has good reliability, and that compared to force plate, acceleration sensor has unacceptable or poor correlation, and gyroscope sensor has mostly fair correlation.

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참고문헌

  1. Nam SM, Na SS, Lee DY. Effects of Otago Exercise program on physical function and risk of falling in the falls experienced elderly. J Korean Acad Nurs. 2020;21(9):424-31.
  2. Park SK, Ryu S, Kim J, Yoon S, Ryu J. Complexity comparison of center of pressure between fallers and non-fallers during gait. KJSB. 2019;29(2):113-9.
  3. Andersen CK, Wittrup-Jensen KU, Lolk A, Andersen K, Kragh-Sorensen P. Ability to perform activities of daily living is the main factor affecting quality of life in patients with dementia. Health Qual. Life Outcomes. 2004;2(1):1-7. https://doi.org/10.1186/1477-7525-2-1
  4. Fall experience of older adults [Internet]. 2018. Available from: https://kosis.kr/statHtml/statHtml.do?orgId=117&tblId=DT_117071_050&conn_path=I.
  5. Nichols DS, Miller L, Colby LA, Pease WS. Sitting balance: its relation to function in individuals with hemiparesis. Arch Phys Med Rehabil. 1996;77(9):865-9. https://doi.org/10.1016/S0003-9993(96)90271-3
  6. Horak FB. Postural orientation and equilibrium: what do we need to know about neural control of balance to prevent falls? Age Ageing. 2006;35(suppl_2):ii7-ii11. https://doi.org/10.1093/ageing/afl077
  7. Kim E. The effect of a virtual reality program on static balance control and fall efficacy of elderly people. J Korean Gerontological Soc. 2010;30:1117-6.
  8. Hwang S, Woo Y. Fall prevention strategies in community-dwelling older adults aged 65 or over with type 2 diabetes mellitus: a systematic review and meta-analysis. Phys Ther Rehabil Sci. 2018;7(4):197-203. https://doi.org/10.14474/ptrs.2018.7.4.197
  9. Yoon S, An H, Ahn T, Choi H, Lee B, Seo D, et al. Performance Evaluation of Balance Ability Equipment Using VR. J Korean soc integr med. 2020;8(3):33-41.
  10. Chang W-D, Chang W-Y, Lee C-L, Feng C-Y. Validity and reliability of wii fit balance board for the assessment of balance of healthy young adults and the elderly. Phys Ther Rehabil Sci. 2013;25(10):1251-3. https://doi.org/10.1589/jpts.25.1251
  11. Chesnin KJ, Selby-Silverstein L, Besser MP. Comparison of an in-shoe pressure measurement device to a force plate: concurrent validity of center of pressure measurements. Gait Posture. 2000;12(2):128-33. https://doi.org/10.1016/S0966-6362(00)00071-0
  12. Hwang J, Hwang S. Smartphone Based Standing Balance Evaluation Using Frequency Domain Analysis of Acceleration. Phys Ther Korea. 2018;25(3):27-38. https://doi.org/10.12674/ptk.2018.25.3.027
  13. Kim JY, Lee KI. Advantages and necessities of telehealth care service. Korean J Med. 2020;95(4):217-27. https://doi.org/10.3904/kjm.2020.95.4.217
  14. Leochico CFD. Adoption of telerehabilitation in a developing country before and during the COVID-19 pandemic. Ann. Phys Rehabil Med. 2020;63(6):563. https://doi.org/10.1016/j.rehab.2020.06.001
  15. An J, Lee BH. Reliability of joint angle during sit-to-stand movements in persons with stroke using portable gait analysis system based wearable sensors. Phys Ther Rehabil Sci. 2019;8(3):146-51. https://doi.org/10.14474/ptrs.2019.8.3.146
  16. Jung SH, Kim SK, Lee JH, Choi SI, Park DS. Reliability and validity of pelvic mobility measurement using a cushion sensor in healthy adults. Phys Ther Rehabil Sci. 2020;9(2):74-81. https://doi.org/10.14474/ptrs.2020.9.2.74
  17. Ferreira CFR. Smartphone Based Tele-Rehabilitation. 2013.
  18. Kim JH, Kim BS, Jeon HM, Kang SY. An LED positioning method using image sensor of a smart device. J-KICS. 2015;40(2):390-6. https://doi.org/10.7840/kics.2015.40.2.390
  19. De Groote F, Vandevyvere S, Vanhevel F, De Xivry J-JO. Validation of a smartphone embedded inertial measurement unit for measuring postural stability in older adults. Gait Posture. 2021;84:17-23. https://doi.org/10.1016/j.gaitpost.2020.11.017
  20. Hou YR, Chiu YL, Chiang SL, Chen HY, Sung WH. Development of a smartphone-based balance assessment system for subjects with stroke. J. Sens. 2019;20(1):88. https://doi.org/10.3390/s20010088
  21. Gabbard C, Hart S. A question of foot dominance. J. Gen. Psychol. 1996;123(4):289-96. https://doi.org/10.1080/00221309.1996.9921281
  22. Nejc, S., Jernej, R., Loefler, S., Kern, H. Sensitivity of body sway parameters during quiet standing to manipulation of support surface size. Journal of Sports Science & Medicine, 9(3), 431.
  23. Lee CH, Sun TL. Evaluation of postural stability based on a force plate and inertial sensor during static balance measurements. J Physiol Anthropol. 2018;37(1):1-16. https://doi.org/10.1186/s40101-017-0162-6
  24. Prosperini L, Fortuna D, Gianni C, Leonardi L, Marchetti MR, Pozzilli C. Home-based balance training using the Wii balance board: a randomized, crossover pilot study in multiple sclerosis. Neurorehabil Neural Repair 2013;27(6):516-25. https://doi.org/10.1177/1545968313478484
  25. Sun R, Moon Y, McGinnis RS, Seagers K, Motl RW, Sheth N, et al. Assessment of postural sway in individuals with multiple sclerosis using a novel wearable inertial sensor. Digit. Biomark. 2018;2(1):1-10. https://doi.org/10.1159/000485958
  26. Chung, C. C., Soangra, R., Lockhart, T. E. Recurrence quantitative analysis of postural sway using force plate and smartphone. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting. Sage CA: Los Angeles, CA: SAGE Publications. 2014;1271-1275.
  27. Jebelli, H., Yang, K., Khalili, M. M., Ahn, C. R., Stentz, T. Assessing the effects of tool-loading formation on construction workers' postural stability. In Construction Research Congress. 2018;292-302.
  28. H. LD, K. HS, J. JH. A study on the reliability of balance abilities measure using a smartphone. J Neurother. 2020;24(2):1-5.
  29. Han SK, Lee IH, Park NR. Reliability of static balance abilities measure using a smartphone's acceleration sensor. J Korean Acad Nurs. 2016;17(6):233-8.
  30. O'sullivan M, Blake C, Cunningham C, Boyle G, Finucane C. Correlation of accelerometry with clinical balance tests in older fallers and non-fallers. Age Ageing. 2009;38(3):308-13.
  31. Koller JR, Jacobs DA, Ferris DP, Remy CD. Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton. J NeuroEng Rehabil. 2015;12(1):1-14. https://doi.org/10.1186/1743-0003-12-1
  32. Mellone S, Tacconi C, Chiari L. Validity of a Smartphone-based instrumented Timed Up and Go. Gait Posture. 2012;36(1):163-5. https://doi.org/10.1016/j.gaitpost.2012.02.006
  33. Lee BC, Kim J, Chen S, Sienko KH. Cell phone based balance trainer. J NeuroEng Rehabil. 2012;9(1):1-14. https://doi.org/10.1186/1743-0003-9-1
  34. Jeremy AP, Amick RZ, Thummar T, Rogers ME. Validation of measures from the smartphone sway balance application: a pilot study. Int J Sports Phys Ther. 2014;9(2):135.
  35. Hou YR, Chiu YL, Chiang SL, Chen HY, Sung WH. Feasibility of a smartphone-based balance as- sessment system for subjects with chronic stroke. Comput Methods Programs Biomed. 2018;161:191-5. https://doi.org/10.1016/j.cmpb.2018.04.027
  36. Park DS, Lee DY, Choi SJ, Shin WS. Reliability and validity of the balancia using wii balance board for assessment of balance with stroke patients. J Korean Acad Nurs. 2013;14(6):2767-72.