skip to main content
10.1145/3154862.3154874acmotherconferencesArticle/Chapter ViewAbstractPublication PagespervasivehealthConference Proceedingsconference-collections
research-article

Examining methods to estimate static body sway from the Kinect V2.0 skeletal data: implications for clinical rehabilitation

Published:23 May 2017Publication History

ABSTRACT

Static body sway is a clinically relevant activity parameter, used to assess postural balance, across a wide spectrum of patient populations. We have examined static body sway using two different segmental total body center of mass (TBCM) estimation methods, the Generator of Body Data III (GEBOD) and Winter's method, using Microsoft Kinect skeletal data. Twenty subjects were recruited through an IRB study and asked to perform three trials of single leg stance with their eyes closed, with positioning based on the Balance Error Scoring System. A force plate system was used to estimate the ground truth data for comparison. Results show that both GEBOD and Winter's method performed similar in estimating anterior-posterior (AP) and medio-lateral (ML) body sway. The results also show highly correlated measurements by the two TBCM estimation methods when compared with the force plate system (mean RMSE value of 10.18 mm square in AP and 8.00 mm square in ML direction). Ordinary Least Square (OLS) linear regressions were performed to improve body sway results obtained from the two methods. Improved sway range values obtained from the simple regression method was able to reduce the estimation errors by 50% (~ 10 mm in both AP and ML body sway). The two static body sway estimation methods were found reliable for obtaining body sway. Thus, the inexpensive, portable Kinect V2.0 can be used for clinical measurements.

References

  1. 2015. BioSway - Biodex.Google ScholarGoogle Scholar
  2. K. Bower, J. Mcginely, K. Miller, and R. A. Clark, 2014. Instrumented static and dynamic balance assessment after stroke using Wii Balance Boards: Reliability and association with clinical tests. PLOS One 9.Google ScholarGoogle Scholar
  3. Brian J. Benda, Patrick O. Riley, and David E. Krebs, 1994. Biomechanical relationship between center of gravity and center of pressure during standing. Ieee Transactions On Rehabilitation Engineering 2, 1.Google ScholarGoogle ScholarCross RefCross Ref
  4. B. Cakmak, A. P. Ribeiro, and A. Inanir, 2015. Postural balance and the risk of falling during pregnancy. J Matern Fetal Neonatal Med(Jul 27), 1--3.Google ScholarGoogle Scholar
  5. Ross A. Clark, Yong-Hao Pua, Karine Fortin, Callan Ritchie, Kate E. Webster, Linda Denehy, and Adam L. Bryant, 2012. Validity of the Microsoft Kinect for assessment of postural control. Gait & Posture 36, 3 (7//), 372--377. DOI= http://dx.doi.org/Google ScholarGoogle Scholar
  6. Ross A. Clark, Stephanie Vernon, Benjamin F. Mentiplay, Kimberly J. Miller, Jennifer L. Mcginley, Yong Hao Pua, Kade Paterson, and Kelly J. Bower, 2015. Instrumenting gait assessment using the Kinect in people living with stroke: reliability and association with balance tests. Journal of NeuroEngineering and Rehabilitation 12, 1, 15.Google ScholarGoogle ScholarCross RefCross Ref
  7. Microsoft Corporation, 2014. Kinect for Windows SDK 2.0 Documentation.Google ScholarGoogle Scholar
  8. D. Lafond, M. Duarte, and F. Prince, 2004. Comparison of three methods to estimate the center of mass during balance assessment. Journal of Biomechanics, 1421--1426.Google ScholarGoogle Scholar
  9. A. González, M. Hayashibe, V. Bonnet, and P. Fraisse, 2014. Whole Body Center of Mass Estimation with Portable Sensors: Using the Statically Equivalent Serial Chain and a Kinect. Sensors (Basel) 14, 9 (Sep), 16955--16971.Google ScholarGoogle ScholarCross RefCross Ref
  10. Mary Earick Gross, 1991. The GEBOD III Program User's Guide and Description. Air Force Systems Command Wright-Patterson Air Force Base, Ohio 45433--6573.Google ScholarGoogle Scholar
  11. Kevin M. Guskiewicz, 2001. Postural Stability Assessment Following Concussion: One Piece of the Puzzle. Clinical Journal of Sport Medicine 11, 3, 182--189.Google ScholarGoogle ScholarCross RefCross Ref
  12. Susan Herdman, 2007. Vestibular Rehabilitation. F.A. Davis Company, Philadelphia.Google ScholarGoogle Scholar
  13. Hyun Gu Kang, Lien Quach, Wenjun Li, and Lewis A. Lipsitz, 2013. Stiffness control of balance during dual task and prospective falls in older adults: The MOBILIZE Boston Study. Gait & Posture 38, 4 (9//), 757--763. DOI= http://dx.doi.org/Google ScholarGoogle Scholar
  14. Priscila Garcia Lopes, Jos Lopes, #Xe9, Augusto Fernandes, Christina Moran Brito, F Alfieri, #Xe1, Bio Marcon, and Linamara Rizzo Battistella, 2015. Relationships of Balance, Gait Performance, and Functional Outcome in Chronic Stroke Patients: A Comparison of Left and Right Lesions. BioMed Research International 2015, 8.Google ScholarGoogle ScholarCross RefCross Ref
  15. Ma Livingston, J Sebastian, Z Ai, and Jw Decker, 2012. Performance Measurements of the Microsoft Kinect Skeleton. In Virtual Reality Short Papers and Posters (VRW). Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. R. N. Madeira, L. Costa, and O. Postolache, 2014. PhysioMate - Pervasive physical rehabilitation based on NUI and gamification. In Electrical and Power Engineering (EPE), 2014 International Conference and Exposition on, 612--616.Google ScholarGoogle Scholar
  17. J.T. Mcconville, I. Churchill, I. K, C. E. Clauser, and J. Cuzzi, 1989. Anthropometric Relationships of Body and Body Segment Moment of Inertia. Aerospace Medical Research Laboratory, Wright-Patterson Air Force Base, Ohio.Google ScholarGoogle Scholar
  18. A. K. Mishra, M. Skubic, and C. Abbott, 2015. Development and preliminary validation of an interactive remote physical therapy system. In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, 190--193.Google ScholarGoogle Scholar
  19. H. Negahban, M. Mazaheri, I. Kingma, and J. H. Van Dieen, 2014. A systematic review of postural control during single-leg stance in patients with untreated anterior cruciate ligament injury. Knee Surg Sports Traumatol Arthrosc 22, 7 (Jul), 1491--1504.Google ScholarGoogle Scholar
  20. Neurocom, 2012. About Neurocom, A Division Of Natus.Google ScholarGoogle Scholar
  21. P. Goldie, T. Bach, and 0. Evans, 1989. Force platform measures for evaluating postural control: Reliability and validit. Arch. Phys. Med. Rehabil. 70, 510--517.Google ScholarGoogle Scholar
  22. M. Patanapanich, V. Vanijja, and P. Dajpratham, 2014. Self-physical rehabilitation system using the microsoft kinect. In Information Technology Systems and Innovation (ICITSI), 2014 International Conference on, 241--247.Google ScholarGoogle Scholar
  23. E. E. Stone and M. Skubic, 2013. Unobtrusive, Continuous, In-Home Gait Measurement Using the Microsoft Kinect. IEEE Transactions on Biomedical Engineering 60, 10, 2925--2932.Google ScholarGoogle Scholar
  24. Vaara M and Karppi S1, 2007. Reliability of functional balance tests measured with posturography in healthy adults. World Congress of Physical Therapy.Google ScholarGoogle Scholar
  25. J. H. Villafane, C. Pirali, R. Buraschi, C. Arienti, C. Corbellini, and S. Negrini, 2015. Moving forward in fall prevention: an intervention to improve balance among patients in a quasi-experimental study of hospitalized patients. Int J Rehabil Res(Jul 30).Google ScholarGoogle Scholar
  26. Qifei Wang, Gregorij Kurillo, Ferda Ofli, and Ruzena Bajcsy, Evaluation of pose tracking accuracy in the first and second generations of Microsoft Kinect. In Proceedings, Intl. Conf. on Healthcare Informatics, 380--389. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. D.A. Winter, 1990. Biomechanics and motor control of human movement. John Wiley & Sons, Inc.Google ScholarGoogle Scholar
  28. Yang Yang, Pu Fang, Li Yan, Li Shuyu, Fan Yubo, and Li Deyu, 2014. Reliability and Validity of Kinect RGB-D Sensor for Assessing Standing Balance. Sensors Journal, IEEE 14, 5, 1633--1638.Google ScholarGoogle Scholar
  29. L. F. Yeung, K. C. Cheng, C. H. Fong, W. C. Lee, and K. Y. Tong, 2014. Evaluation of the Microsoft Kinect as a clinical assessment tool of body sway. Gait Posture 40, 4 (Sep), 532--538.Google ScholarGoogle ScholarCross RefCross Ref
  30. Young, Joseph W., Richard F., C. C. Chandler, Kathleen M. R., Gregory F. Z., and Maureen S. L., 1983. Anthropometric and Mass Distribution Characteristics of the Adult Female, Civil Aeromedical Institute, Federal Aviation Administration, Oklahoma City, Oklahoma.Google ScholarGoogle Scholar
  31. V. M. Zatsiorsky and M. Duarte, 2000. Rambling and trembling in quiet standing. Motor Control 4, 2 (Apr), 185--200.Google ScholarGoogle ScholarCross RefCross Ref

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    PervasiveHealth '17: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare
    May 2017
    503 pages
    ISBN:9781450363631
    DOI:10.1145/3154862

    Copyright © 2017 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 23 May 2017

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • research-article

    Acceptance Rates

    Overall Acceptance Rate55of116submissions,47%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader