Journal of Medical Research and Development          
Journal of Medical Research and Development(JMRD)
Frequency: Quarterly
Evaluation of Kinect as an Analysis Tool for Kinematic Variables of Shoulder and Spine Motions
Full Paper(PDF, 876KB)
Specific kinematic actions of the spine and shoulder are useful for low back pain (LBP) assessment and treatment. However, the widespread application of motion capture systems in clinical settings is limited by the tedious process and expensive equipment. As a cost-effective and portable device, Kinect has the potential to be used in clinical analysis and rehabilitation for patients with LBP. Using Kinect and a motion capture system, 10healthysubjectsperformed left/right bending and extension tasks five times successively with and without simulated motion limitations. The mean range of motion (ROM)and maximum angular velocity (MAV) were then calculated. The results revealed that the Pearson's correlation coefficient was more than 0.7 with ROM. The root-mean-square error (RMSE) of the ROM difference, with and without motion limitation, was1.2–3 (for MAV: 4.7/s–14.6/s). In conclusion, Kinect can be used as an analysis tool for kinematic variability of shoulder and trunk motion, which could help obtain low back information regarding movement patterns and strategies under various movement tasks.
Keywords:Low Back Pain; Kinect; Assessment; Motion Capture; Range of Motion; Maximum Angular Velocity
Author: Zengwu Duan1, Jinzhuang Xiao1, Hongrui Wang1
1.College of Electronic and Information Engineering, Hebei University, Baoding, China
  1. J. N. Katz, “Lumbar disc disorders and low-back pain: Socioeconomic factors and consequences,” Journal of Bone & Joint Surgery-American, vol. 88, suppl. 2, pp. 21-24, 2006.
  2. N. J.Manek and A. J. Macgregor, “Epidemiology of back disorders: Prevalence, risk factors, and prognosis,” Current Opinion in Rheumatology, vol. 17, iss. 2, pp. 134-140, 2005.
  3. G. Pransky, R. Buchbinder, and J. Hayden, “Contemporary low back pain research – and implications for practice,” Best Practice & Research Clinical Rheumatology, vol. 24, iss. 2, pp. 291-298, 2010.
  4. H. Robin, P. G. Osmotherly, and D. A. Rivett, “Validation and impact analysis of prognostic clinical prediction rules for low back pain is needed: A systematic review,” Journal of Clinical Epidemiology, vol. 68, iss. 7, pp. 821-832, 2015.
  5. P. S. Sung, “A kinematic analysis for shoulder and pelvis coordination during axial trunk rotation in subjects with and without recurrent low back pain,” Gait & Posture, vol. 40, iss. 4, pp. 493-498, 2014.
  6. W. V. D. Hoorn, S. M. Bruijn, O. G. Meijer, P. W. Hodges, and J. H. V. Dieen, “Mechanical coupling between transverse plane pelvis and thorax rotations during gait is higher in people with low back pain,” Journal of Biomechanics, vol. 45, iss. 2, pp. 342-347, 2012.
  7. I. Bourigua, E. M. Simoneau, S. Leteneur, C. Gillet, and G. Ido, “Chronic low back pain sufferers exhibit freezing-like behaviours when asked to move their trunk as fast as possible,” Spine Journal Official Journal of the North American Spine Society, vol. 14, iss. 7, pp. 1291-1299, 2014.
  8. L. F. Yeung, K. C. Cheng, C. H. Fong, W. C. Lee, and K. Tong, “Evaluation of the Microsoft Kinect as a clinical assessment tool of body sway,” Gait & Posture, vol. 40, iss. 4, pp. 532-538, 2014.
  9. A. Y. Song, H. J. Jo, P. S. Sung, and Y. H. Kim, “Three-dimensional kinematic analysis of pelvic and lower extremity differences during trunk rotation in subjects with and without chronic low back pain,” Physiotherapy, vol. 98, iss. 2, pp. 160-166, 2012.
  10. M. G. Boocock, G. A. Mawston, and S. Taylor, “Age-related differences do affect postural kinematics and joint kinetics during repetitive lifting,” Clinical Biomechanics, vol. 30, pp. 136-143, 2015.
  11. Y. J. Chang, S. F. Chen, and A. F. Chuang, “A gesture recognition system to transition autonomously through vocational tasks for individuals with cognitive impairments,” Research in Developmental Disabilities a Multidisciplinary Journal, vol. 32, iss. 6, pp. 2064-2068, 2011.
  12. Y. J. Chang, S. F. Chen, and J. Huang, “A Kinect-based system for physical rehabilitation: A pilot study for young adults with motor disabilities,” Research in Developmental Disabilities, vol. 32, iss. 6, pp. 2566-2570, 2011.
  13. B. Bonnechère, B. Jansen, P. Salvia, H. Bouzahouene, L. Omelina, F. Moiseev, and et al., “Validity and reliability of the Kinect within functional assessment activities: comparison with standard stereophotogrammetry,” Gait & Posture, vol. 39, iss. 1, pp. 593-598, 2014.
  14. R. A. Clark, “Validity of the Microsoft Kinect for assessment of postural control,” Gait & Posture, vol. 36, iss. 3, pp. 372-377, 2012.
  15. Y. J. Chang, W. Y Han, and T. Yc, “A Kinect-based upper limb rehabilitation system to assist people with cerebral palsy,” Research in Developmental Disabilities, vol. 34, iss. 11, pp. 3654-3659, 2013.
  16. N. Vernadakis,“The effect of Xbox Kinect intervention on balance ability for previously injured young competitive male athletes a preliminary study,” Physical Therapy in Sport Official Journal of the Association of Chartered Physiotherapists in Sports Medicine, vol. 15, iss. 3, pp. 148-155, 2014.
  17. R. A. Clark, “Concurrent validity of the Microsoft Kinect for assessment of spatiotemporal gait variables,” Journal of Biomechanics, vol. 46, iss. 15, pp. 2722-2725, 2013.
  18. J. L. Fleiss, “The design and analysis of clinical experiments,” Sons Friedman Lm Furberg Cd Demets Dl Fundamentals A/clinical Trials Edn, vol. 8, pp.791-791, 1986.
  19. T. R. Derrick, B. T. Bates, and J. S.Dufek, “Evaluation of time-series data sets using the Pearson product-moment correlation coefficient,” Medicine & Science in Sports & Exercise, vol. 26, iss. 7, pp. 919-928, 1994.
  20. M. T. Puth, M. Neuhauser, and G. D. Ruxton, “Effective use of Pearson's product-moment correlation coefficient comment,” Animal Behaviour, vol. 93, pp. 183-189,2014.
  21. P. S. Sung, “A kinematic analysis for shoulder and pelvis coordination during axial trunk rotation in subjects with and without recurrent low back pain,” Gait & Posture, vol. 40, iss. 4, pp. 493-498, 2014.
  22. K. Khoshelham and S. O. Elberink, “Accuracy and resolution of Kinect depth data for indoor mapping applications,” Sensors, vol. 12, iss. 2, pp. 1437-1454, 2012.
  23. C. H. Shih, “A new limb movement detector enabling people with multiple disabilities to control environmental stimulation through limb swing with a gyration air mouse,” Research in Developmental Disabilities a Multidisciplinary Journal, vol. 31, iss. 4, pp. 875-880, 2010.