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Test-Retest and Intra-rater Reliability of Using Inertial Sensors and Its Integration with Microsoft Kinect™ to Measure Shoulder Range-of-Motion

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Internet of Things Technologies for HealthCare (HealthyIoT 2016)

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Abstract

This study determined the intra-rater and test-retest reliability of a novel motion-tracking system that integrates inertial sensors with Microsoft Kinect to measure peak shoulder range-of-motion (ROM) angles. Nine healthy individuals (6 female and 3 male, age: 36.6 ± 13.3) with no shoulder pathology participated following ethical approval. Participants performed active shoulder forward flexion and abduction to the end of available range. Repeat testing of the protocol was completed after 7 days by the same rater. Results demonstrated excellent intra-rater reliability (ICC = 0.84, 0.93) for shoulder flexion and modest-excellent intra-rater reliability (ICC = 0.82, 0.52) for shoulder abduction. A high level of correlation was observed between week 1 and 2 for flexion and abduction (R = 0.85 – 0.93), expect for left abduction (R = 0.60). In conclusion, an inertial system combined with the Kinect is a reliable tool to measure shoulder ROM and has the potential for future research and clinical application.

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References

  1. Muir, S.W., Corea, C.L., Beaupre, L.: Evaluating change in clinical status: reliability and measures of agreement for the assessment of glenohumeral range of motion. North Am. J. Sports Phys. Ther. NAJSPT 5, 98–110 (2010)

    Google Scholar 

  2. American Academy of Orthopaedic Surgeons. Joint motion: method of measuring and recording. AAOS, Chicago (1965)

    Google Scholar 

  3. Mullaney, M.J., McHugh, M.P., Johnson, C.P., Tyler, T.F.: Reliability of shoulder range of motion comparing a goniometer to a digital level. Physiother. Theory Pract. 26(5), 327 (2010)

    Article  Google Scholar 

  4. Riddle, D.L., Rothstein, J.M., Lamb, R.L.: Goniometric reliability in a clinical setting. Shoulder Measur. Phys. Ther. 67(5), 668–673 (1987)

    Google Scholar 

  5. Hayes, K., Walton, J.R., Szomor, Z.R., Murrell, G.A.: Reliability of five methods for assessing shoulder range of motion. Austr. J. Physiother. 47(4), 289–294 (2001)

    Article  Google Scholar 

  6. Willams, J.G., Callaghan, M.: Comparison of visual estimation and goniometry in determination of shoulder angle. Physiotherapy 76(10), 655–657 (1990)

    Article  Google Scholar 

  7. Terwee, C.B., de Winter, A.F., Scholten, R.J., Jans, M.P., Deville, W., van Schaardenburg, D., Bouter, L.M.: Interobserver reproducibility of the visual estimation of range of motion of the shoulder. Arch. Phys. Med. Rehabil. 86(7), 1356–1361 (2005)

    Article  Google Scholar 

  8. Chen, J.F., Ginn, K.A., Herbert, R.D.: Passive mobilisation of shoulder region joints plus advice and exercise does not reduce pain and disability more than advice and exercise alone: a randomised trial. Austr. J. Physiother. 55(1), 17–23 (2009)

    Article  Google Scholar 

  9. Ginn, K.A., Herbert, R.D., Khouw, W., Lee, R.A.: Randomised controlled trial of a treatment of shoulder pain. Phys. Ther. 77, 802–809 (1997)

    Google Scholar 

  10. Mitchell, K., Gutierrez, S.B., Sutton, S., Morton, S., Morgenthaler, A.: Reliability and validity of goniometric iPhone applications for the assessment of active shoulder external rotation. Physiother. Theory Pract. 30(7), 521–525 (2014)

    Article  Google Scholar 

  11. El-Gohary, M., McNames, J.: Human joint angle estimation with inertial sensors and validation with a robot arm. IEEE Trans. Biomed. Eng. 62(7), 1759–1767 (2015)

    Article  Google Scholar 

  12. Zhou, H., Stone, T., Huosheng, H., Harris, N.: Use of multiple wearable inertial sensors in upper limb motion tracking. Med. Eng. Phys. 30(I), 123–133 (2008)

    Article  Google Scholar 

  13. Coley, B., Jolles, B.M., Farron, A., Bourgeois, A., Nussbaumer, F., Pichonnaz, C., Aminian, K.: Outcome evaluation in shoulder surgery using 3D kinematics sensors. Gait Posture 27, 368–375 (2007)

    Article  Google Scholar 

  14. Luinge, H., Veltink, P., Baten, C.: Ambulatory measurement of arm orientation. J. Biomech. 40, 78–85 (2007)

    Article  Google Scholar 

  15. Teece, R., Lunden, J., Lloyd, A., Kaiser, A., Cieminski, C., Ludewig, P.: Three-dimensional acromioclavicular joint motions during elevation of the arm. J. Ortho. Sports Phys. Ther. 38(4), 181–190 (2008)

    Article  Google Scholar 

  16. Paulis, W.D., Horemans, H.L., Brouwer, B.S., Stam, H.J.: Excellent test-retest and inter-rater reliability for Tardieu Scale measurements with inertial sensors in elbow flexors of stroke patients. Gait Posture 33(2), 185–189 (2011)

    Article  Google Scholar 

  17. Hawi, N., Liodakis, E., Musolli, D., Suero, E.M., Stuebig, T., Claassen, L., Kleiner, C., Krettek, C., Ahlers, V., Citak, M.: Range of motion assessment of the shoulder and elbow joints using a motion sensing input device a pilot study. Technol. Health Care: Offic. J. Eur. Soc. Eng. Med. 22(2), 289–295 (2014)

    Google Scholar 

  18. Matsen III, F.A., Lauder, A., Rector, K., Keeling, P., Cherones, A.L.: Measurement of active shoulder motion using the Kinect, a commercially available infrared position detection system. J. Shoulder Elbow Surg. 25(2), 216–223 (2016)

    Article  Google Scholar 

  19. Nixon, M.E., Howard, A.M, Yu-Ping, C.: Quantitative evaluation of the Microsoft Kinect for use in an upper extremity virtual rehabilitation environment. In: International Conference on Virtual Rehabilitation (ICVR), 26–29 August 2013

    Google Scholar 

  20. Huber, M.E., Seitz, A.L., Leeser, M., Sternad, D.: Validity and reliability of Kinect skeleton for measuring shoulder joint angles: a feasibility study. Physiotherapy 101(4), 389–393 (2015)

    Article  Google Scholar 

  21. Lee, S.H., Yoon, C., Chung, S.G., Kim H.C., Kwak, Y., Park, H.W., Kim, K.: Measurement of shoulder range of motion in patients with adhesive capsulitis. PLoS One 10(6) (2015)

    Google Scholar 

  22. Bo, A., Hayashibe, M., Poignet, P.: Joint angle estimation in rehabilitation with inertial sensors and its integration with Kinect. In: 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2011, pp. 3479–3483. IEEE Press, Boston (2011)

    Google Scholar 

  23. Fleiss, J.L.: The Design and Analysis of Clinical Experiments. Wiley Series in Probability and Mathematical statistics Applied Probability and Statistics, p. xiv-432. Wiley, New York (1986)

    Google Scholar 

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Authors and Affiliations

  1. Physiotherapy Department, Prince of Wales Clinical School, Prince of Wales Hospital, UNSW Australia, High Street, Randwick, Sydney, 2031, Australia

    Peter Beshara, Judy Chen, Pierre Lagadec & W. R. Walsh

Authors
  1. Peter Beshara
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  2. Judy Chen
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  3. Pierre Lagadec
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  4. W. R. Walsh
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Corresponding author

Correspondence to Peter Beshara .

Editor information

Editors and Affiliations

  1. School Innovation, Design, Engineering, Märlardalen University, Västerås, Sweden

    Mobyen Uddin Ahmed

  2. Mälardalen University , Västerås, Sweden

    Shahina Begum

  3. Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    Wasim Raad

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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Beshara, P., Chen, J., Lagadec, P., Walsh, W.R. (2016). Test-Retest and Intra-rater Reliability of Using Inertial Sensors and Its Integration with Microsoft Kinect™ to Measure Shoulder Range-of-Motion. In: Ahmed, M., Begum, S., Raad, W. (eds) Internet of Things Technologies for HealthCare. HealthyIoT 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 187. Springer, Cham. https://doi.org/10.1007/978-3-319-51234-1_31

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  • DOI: https://doi.org/10.1007/978-3-319-51234-1_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51233-4

  • Online ISBN: 978-3-319-51234-1

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