The Development and Evaluation of an Interactive System for Age Related Musculoskeletal Rehabilitation in the Home

  • Mobolaji Ayoade
  • Stephen Uzor
  • Lynne Baillie
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8120)


This paper describes a series of user studies carried out to investigate the usability, significance, and acceptance of two visualization tools designed to improve the quality of, and adherence to home-based exercise programmes for musculoskeletal rehabilitation. The core functionality of these visualization tools enabled the users to observe the optimal way to perform their exercises via a mannequin, and receive feedback on their own movements through the use of body worn sensors. Before full deployment in the home, two user studies were carried out in the laboratory, and then two in the home with seniors who had recently undergone musculoskeletal rehabilitation using a standard care paper based booklet in the home. Our key findings suggest that by using the visualization tools the participants were able to overcome the major limitations of standard care; and that these tools were considered by the users to be useful in encouraging participation in home exercise.


Home rehabilitation inertial motion sensors older adults visualizations and musculoskeletal conditions 


  1. 1.
    Woolf, A.D., Pfleger, B.: Burden of major musculoskeletal conditions. Bull. World Health Organ. 81, 646–656 (2003)Google Scholar
  2. 2.
    Scottish Arthroplasty Project Biennial Report 2012, NHS National Services Scotland, p. 9,
  3. 3.
    Skelton, D., Todd, C.: What are the main risk factors for falls among older people and what are the most effective interventions to prevent these falls? Copenhagen, WHO Regional Office for Europe (2004),
  4. 4.
    Thomas, S., Mackintosh, S., Halbert, J.: Does the ‘Otago exercise programme’ reduce mortality and falls in older adults?: a systematic review and meta-analysis. Age Ageing 39(6), 681–687 (2010)CrossRefGoogle Scholar
  5. 5.
    Applegate, W.B., Miller, S.T., Graney, M.J., Elam, J.T., Burns, R., Akins, D.E.: A Randomized, Controlled Trial of a Geriatric Assessment Unit in a Community Rehabilitation Hospital. New England Journal of Medicine 322, 1572–1578 (1990)CrossRefGoogle Scholar
  6. 6.
    Medical Advisory Secretariat: Physiotherapy rehabilitation after total knee or hip replacement: an evidence-based analysis. Ontario Health Technology Assessment Series 5(8) (2005)Google Scholar
  7. 7.
    Nyman, S.R., Victor, C.R.: Older people’s participation in and engagement with falls prevention interventions in community settings: An augment to the Cochrane systematic review. Age Ageing (2011),
  8. 8.
    Pisters, M.F., Veenhof, C., Schellevis, F.G., Twisk, J.W.R., Dekker, J., De Bakker, D.H.: Exercise adherence improving long-term patient outcome in patients with osteoarthritis of the hip and/or knee. Arthritis Care & Research 62, 1087–1094 (2010)CrossRefGoogle Scholar
  9. 9.
    Scott, J.C.: Osteoporosis and hip fractures. Rheumatic Diseases Clinics of North America 16(3), 717–740 (1990)Google Scholar
  10. 10.
    Fessel, K., Nevitt, M.: Correlates of fear of falling and activity limitation among persons with rheumatoid arthritis. Arthritis Care and Research 10(4), 222–228 (1997)CrossRefGoogle Scholar
  11. 11.
    Button, K., Iqbal, A.S., Letchford, R.H., Van Deursen, R.W.M.: Clinical effectiveness of knee rehabilitation techniques and implications for a self-care treatment model. Physiotherapy 98, 287–299 (2012)CrossRefGoogle Scholar
  12. 12.
    Wheeler, J.W., Shull, P.B., Besier, T.F.: Real-Time Knee Adduction Moment Feedback for Gait Retraining Through Visual and Tactile Displays. Journal of Biomechanical Engineering 133, 041007 (2011)Google Scholar
  13. 13.
    Walker, C., Brouwer, B.J., Culham, E.G.: Use of visual feedback in retraining balance following acute stroke. Phys. Ther. 80, 886–895 (2000)Google Scholar
  14. 14.
    Zhou, Hu, H.: Human motion tracking for rehabilitation—A survey. Biomedical Signal Processing and Control 3, 1–18 (2008)CrossRefGoogle Scholar
  15. 15.
    Uzor, S., Baillie, L., Skelton, D., Fairlie, F.: Identifying barriers to effective user interaction with rehabilitation tools in the home. In: Campos, P., Graham, N., Jorge, J., Nunes, N., Palanque, P., Winckler, M. (eds.) INTERACT 2011, Part II. LNCS, vol. 6947, pp. 36–43. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  16. 16.
    Suttanon, P., Hill, K.D., Said, C.M., Byrne, K.N., Dodd, K.J.: Factors influencing commencement and adherence to a home-based balance exercise program for reducing risk of falls: perceptions of people with Alzheimer’s disease and their caregivers. International Psychogeriatrics 24, 1172–1182 (2012)CrossRefGoogle Scholar
  17. 17.
    Lim, C.K., Chen, I.-M., Luo, Z., Yeo, S.H.: A low cost wearable wireless sensing system for upper limb home rehabilitation. In: 2010 IEEE Conference on Robotics Automation and Mechatronics (RAM), pp. 1–8 (2010)Google Scholar
  18. 18.
    Doyle, J., Bailey, C., Dromey, B., Scanaill, C.N.: BASE - An interactive technology solution to deliver balance and strength exercises to older adults. In: 4th International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth, pp. 1–5 (2010)Google Scholar
  19. 19.
    Harms, M.: Advancing technology in rehabilitation. Physiotherapy 98, 181–182 (2012)CrossRefGoogle Scholar
  20. 20.
    Tanaka, K., Parker, J., Baradoy, G., Sheehan, D., Holash, J.R., Katz, L.: A Comparison of Exergaming Interfaces for Use in Rehabilitation Programs and Research. LDG 6, 69–81 (2012)Google Scholar
  21. 21.
    Gerling, K.M., Schulte, F.P., Masuch, M.: Designing and evaluating digital games for frail elderly persons. In: Proc. of ACE 2011 (2011)Google Scholar
  22. 22.
    Borghese, N.A., Pirovano, M., Mainetti, R., Lanzi, P.L.: An integrated low-cost system for at-home rehabilitation. In: 2012 18th International Conference on Virtual Systems and Multimedia, VSMM, pp. 553–556 (2012)Google Scholar
  23. 23.
    Theng, Y.-L., Dahlan, A.B., Akmal, M.L., Myint, T.Z.: An exploratory study on senior citizens’ perceptions of the Nintendo Wii: the case of Singapore, pp. 1–5. ACM, Singapore (2009)Google Scholar
  24. 24.
    Fung, V., Ho, A., Shaffer, J., Chung, E., Gomez, M.: Use of Nintendo Wii FitTM in the rehabilitation of outpatients following total knee replacement: a preliminary randomised controlled trial. Physiotherapy 98, 183–188 (2012)CrossRefGoogle Scholar
  25. 25.
    Ziefle, M., Röcker, C.: User Diversity as a Challenge for the Integration of Medical Technology into Future Smart Home Environments. In: Human-Centered Design of E-Health Technologies, pp. 95–126. IGI Global, USA (2010)CrossRefGoogle Scholar
  26. 26.
  27. 27.
    JointPathwaysTM Patient Guides for Knees, Golden Jubilee National Hospital NHS ScotlandGoogle Scholar
  28. 28.
    Age UK. Preventing Falls: Strength and balance exercises for healthy ageing (2011),
  29. 29.
    Hondori, M.H., Khademi, M., Lopes, C.V.: Monitoring Intake Gestures using Sensor Fusion (Microsoft Kinect and Inertial Sensors) for Smart Home Tele-Rehab Setting (2012),
  30. 30.
    Bo, A.P.L., Hayashibe, M., Poignet, P.: Joint angle estimation in rehabilitation with inertial sensors and its integration with Kinect. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, pp. 3479–3483 (2011)Google Scholar
  31. 31.
    Uzor, S., Baillie, L., Skelton, D.: Senior designers: empowering seniors to design enjoyable falls rehabilitation tools. In: Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems, pp. 1179–1188 (2012)Google Scholar
  32. 32.
    Loudon, D., Macdonald, A.S., Carse, B., Thikey, H., Jones, L., Rowe, P.J., Uzor, S., Ayoade, M., Baillie, L.: Developing visualisation software for rehabilitation: Investigating the requirements of patients, therapists and the rehabilitation process. Health Informatics Journal 18, 171–180 (2012)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mobolaji Ayoade
    • 1
  • Stephen Uzor
    • 1
  • Lynne Baillie
    • 1
  1. 1.Interactive and Trustworthy Technologies Group, School of Engineering and Built EnvironmentGlasgow Caledonian UniversityUK

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