Journal of Korean Physical Therapy Science (대한물리치료과학회지)

Korean Physical Therapy Science (대한물리치료과학회)
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The test-retest reliability of gait kinematic data measured using a portable gait analysis system in healthy adults

  • Received : 2020.08.06
  • Accepted : 2020.09.21
  • Published : 2020.12.31
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Abstract

Background: Gait analysis is an important measurement for health professionals to assess gait patterns related to functional limitations due to neurological or orthopedic conditions. The purpose of this study was to investigate the reliability of the newly developed portable gait analysis system (PGAS). Design: Cross-sectional design. Test-retest study. Methods: The PGAS study was based on a wearable sensor, and measurement of gait kinematic parameters, such as gait velocity, cadence, step length and stride length, and joint angle (hip, knee, and ankle) in stance and swing phases. The results were compared with a motion capture system (MCS). Twenty healthy individuals were applied to the MCS and PGAS simultaneously during gait performance. Results: The test-retest reliability of the PGAS showed good repeatability in gait parameters with mean intra-class correlation coefficients (ICCs) ranging from 0.840 to 0.992, and joint angles in stance and swing phase from 0.907 to 0.988. The acceptable test-retest ICC was observed for the gait parameters (0.809 to 0.961), and joint angles (0.800 to 0.977). Conclusion: The results of this study indicated that the developed PGAS showed good grades of repeatability for gait kinematic data along with acceptable ICCs compared with the results from the MCS. The gait kinematic parameters in healthy subjects can be used as standard values for adopting this PGAS.

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References

  1. Alandry B, Dumas N, Latorre L, et al. A CMOS multi-sensor system for 3D orientation determination. In 2008 IEEE Computer Society Annual Symposium on VLSI. IEEE; 2008. p.57-62.
  2. Dorociak RD, Cuddeford TJ. Determining 3-D system accuracy for the VICON 370 system. Gait Posture 1995;3(2):88. https://doi.org/10.1016/0966-6362(95)93468-R
  3. Dobkin BH, Firestine A, West M, et al. Ankle dorsiflexion as an fMRI paradigm to assay motor control for walking during rehabilitation. Neuroimage 2004;23(1):370-81. https://doi.org/10.1016/j.neuroimage.2004.06.008
  4. Eigster M. Reliability assessment of a Qualisys 3D gait analysis system [Unpublished doctoral dissertation]. University of Iceland; 2010.
  5. Gharib NM, Adel SM, Kishk NA. Reliability of three-dimensional motion analysis in assessment of Bell's palsy. J Am Sci 2011;7(9):126-34.
  6. Ghoussayni S, Stevens C, Durham S, et al. Assessment and validation of a simple automated method for the detection of gait events and intervals. Gait Posture 2004;20(3):266-72. https://doi.org/10.1016/j.gaitpost.2003.10.001
  7. Guo Y, Wu D, Liu G, et al. A low-cost body inertial-sensing network for practical gait discrimination of hemiplegia patients. Telemed J E Health 2012;18(10):748-54. https://doi.org/10.1089/tmj.2012.0014
  8. Kim S, Nussbaum MA. Evaluation of two approaches for aligning data obtained from a motion capture system and an in-shoe pressure measurement system. Sensors (Basel) 2014;14(9):16994-7007. https://doi.org/10.3390/s140916994
  9. Kok M, Hol JD, Schon TB, et al. Calibration of a magnetometer in combination with inertial sensors. In 2012 15th International Conference on Information Fusion. IEEE; 2012. p.787-93.
  10. Kun L, Inoue Y, Shibata K, et al. Ambulatory estimation of knee-joint kinematics in anatomical coordinate system using accelerometers and magnetometers. IEEE Trans Biomed Eng 2011;58(2):435-42. https://doi.org/10.1109/TBME.2010.2089454
  11. Lopez-Meyer P, Fulk GD, Sazonov ES. Automatic detection of temporal gait parameters in poststroke individuals. IEEE Trans Inf Technol Biomed 2011;15(4):594-601. https://doi.org/10.1109/TITB.2011.2112773
  12. Park J, Kim E, Yang S, et al. Effects of Random Visual and Auditory Stimulation on Walking of Healthy Adults. J Korean Phys Ther Sci 2019;26(1):35-44. https://doi.org/10.26862/jkpts.2019.06.26.1.35
  13. Tadano S, Takeda R, Miyagawa H. Three dimensional gait analysis using wearable acceleration and gyro sensors based on quaternion calculations. Sensors(Basel) 2013;13(7):9321-43. https://doi.org/10.3390/s130709321
  14. Tao W, Liu T, Zheng R, et al. Gait analysis using wearable sensors. Sensors(Basel) 2012;12(2):2255-2283.
  15. Wagner R, Ganz A. PAGAS: Portable and accurate gait analysis system. Conf Proc IEEE Eng Med Biol Soc 2012;280-3.
  16. Windolf M, Götzen N, Morlock M. Systematic accuracy and precision analysis of video motion capturing systems--exemplified on the Vicon-460 system. J Biomech 2008;41(12):2776-80. https://doi.org/10.1016/j.jbiomech.2008.06.024
  17. Yavuzer G, Oken O, Elhan A, et al. Repeatability of lower limb three-dimensional kinematics in patients with stroke. Gait Posture 2008;27(1):31-5. https://doi.org/10.1016/j.gaitpost.2006.12.016