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A Peripheral Tactile Feedback System for Lateral Epicondilytus Rehabilitation Exercise

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Published:08 May 2021Publication History

ABSTRACT

Lateral epicondilytus (LE), or tennis elbow, is a highly prevalent musculoskeletal condition that affects millions of people. Physiotherapy is a common treatment, with a large portion consisting of prescribed home-based exercises. Adherence to these programs is an important factor in rehabilitation, however there are many barriers to adherence including the exercise taking up too much of the patient’s attention, or the patient feeling like they are not carrying out exercises correctly. To address these problems, this paper describes a prototype system that uses haptic feedback to guide the patient to correctly carry out a commonly prescribed LE rehabilitation exercise, while allowing them to attend to external information such as another person or a screen. The system peripherally conveys information about the speed of movement and position of the user’s wrist movement via peripheral vibration feedback, allowing the user to make adjustments to movement whilst keeping the visual and auditory senses free to attend to other sources. Finally, we discuss future areas of research for this prototype and applications of vibrotactile feedback for physiotherapy in general.

References

  1. Omid Alizadehkhaiyat, Anthony C Fisher, Graham J Kemp, and Simon P Frostick. 2007. Pain, functional disability, and psychologic status in tennis elbow. The Clinical journal of pain 23, 6 (2007), 482–489.Google ScholarGoogle Scholar
  2. Mobolaji Ayoade and Lynne Baillie. 2014. A novel knee rehabilitation system for the home. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems. ACM, 2521–2530.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. S Frances Bassett. 2003. The assessment of patient adherence to physiotherapy rehabilitation. New Zealand journal of physiotherapy 31, 2 (2003), 60–66.Google ScholarGoogle Scholar
  4. Leanne Bisset, Elaine Beller, Gwendolen Jull, Peter Brooks, Ross Darnell, and Bill Vicenzino. 2006. Mobilisation with movement and exercise, corticosteroid injection, or wait and see for tennis elbow: randomised trial. Bmj 333, 7575 (2006), 939.Google ScholarGoogle Scholar
  5. R Campbell, M Evans, M Tucker, B Quilty, P Dieppe, and JL Donovan. 2001. Why don’t patients do their exercises? Understanding non-compliance with physiotherapy in patients with osteoarthritis of the knee. Journal of Epidemiology & Community Health 55, 2 (2001), 132–138.Google ScholarGoogle ScholarCross RefCross Ref
  6. Sebastian Deterding, Miguel Sicart, Lennart Nacke, Kenton O’Hara, and Dan Dixon. 2011. Gamification. using game-design elements in non-gaming contexts. In CHI’11 extended abstracts on human factors in computing systems. 2425–2428.Google ScholarGoogle Scholar
  7. Jamie Ferguson, John Williamson, and Stephen Brewster. 2018. Evaluating mapping designs for conveying data through tactons. In Proceedings of the 10th Nordic Conference on Human-Computer Interaction. ACM, 215–223.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Ernesto Filgueiras and Gustavo Desouzart. 2020. Gamedesign and Physiotherapy: Contribution of Gamification and UX Techniques to Physical Teenagers’ Recovery. In International Conference on Human-Computer Interaction. Springer, 216–228.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Theodoros Georgiou, Riasat Islam, Simon Holland, Janet Van Der Linden, Blaine Price, Paul Mulholland, and Allan Perry. 2020. Rhythmic Haptic Cueing Using Wearable Devices as Physiotherapy for Huntington Disease: Case Study. JMIR Rehabilitation and Assistive Technologies 7, 2(2020), e18589.Google ScholarGoogle ScholarCross RefCross Ref
  10. Darren C.R. Goh, Alfred C.H. Tan, and Jeannie S.A. Lee. 2017. Gamification of Heel Raise Plantarflexion Physiotherapy. In Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care(Mountain View, California, USA) (MMHealth ’17). Association for Computing Machinery, New York, NY, USA, 35–43. https://doi.org/10.1145/3132635.3132638Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Chelsea Hopkins, Sai-Chuen Fu, Eldrich Chua, Xiaorui Hu, Christer Rolf, Ville M Mattila, Ling Qin, Patrick Shu-Hang Yung, and Kai-Ming Chan. 2016. Critical review on the socio-economic impact of tendinopathy. Asia-Pacific Journal of Sports Medicine, Arthroscopy, Rehabilitation and Technology 4(2016), 9–20.Google ScholarGoogle Scholar
  12. Kirsten Jack, Sionnadh Mairi McLean, Jennifer Klaber Moffett, and Eric Gardiner. 2010. Barriers to treatment adherence in physiotherapy outpatient clinics: a systematic review. Manual therapy 15, 3 (2010), 220–228.Google ScholarGoogle Scholar
  13. Ard Jacobs, Annick Timmermans, Marc Michielsen, Maaiken Vander Plaetse, and Panos Markopoulos. 2013. CONTRAST: gamification of arm-hand training for stroke survivors. In CHI’13 Extended Abstracts on Human Factors in Computing Systems. 415–420.Google ScholarGoogle Scholar
  14. Val Jones. 2009. Physiotherapy in the management of tennis elbow: a review. Shoulder & Elbow 1, 2 (2009), 108–113.Google ScholarGoogle ScholarCross RefCross Ref
  15. Jussi Kasurinen and Antti Knutas. 2018. Publication trends in gamification: A systematic mapping study. Computer Science Review 27 (2018), 33–44.Google ScholarGoogle ScholarCross RefCross Ref
  16. Robert W Lindeman, Yasuyuki Yanagida, Kenichi Hosaka, and Shinji Abe. 2006. The TactaPack: A wireless sensor/actuator package for physical therapy applications. In Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2006 14th Symposium on. IEEE, 337–341.Google ScholarGoogle ScholarCross RefCross Ref
  17. Nathanael Macdonald, Caterina Clements, Anshul Sobti, Daniel Rossiter, Ashwin Unnithan, and Nicholas Bosanquet. 2020. Tackling the elective case backlog generated by Covid-19: the scale of the problem and solutions. Journal of Public Health 42, 4 (2020), 712–716.Google ScholarGoogle ScholarCross RefCross Ref
  18. Shaun Alexander Macdonald and Stephen Brewster. 2019. Gamification of a To-Do List with Emotional Reinforcement. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. 1–6.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Rui Neves Madeira, Luís Costa, and Octavian Postolache. 2014. PhysioMate-Pervasive physical rehabilitation based on NUI and gamification. In 2014 International Conference and Exposition on Electrical and Power Engineering (EPE). IEEE, 612–616.Google ScholarGoogle ScholarCross RefCross Ref
  20. M Nelson, M Bourke, K Crossley, and T Russell. 2020. Telerehabilitation is non-inferior to usual care following total hip replacement—a randomized controlled non-inferiority trial. Physiotherapy 107(2020), 19–27.Google ScholarGoogle ScholarCross RefCross Ref
  21. Adria Quigley, Helen Johnson, and Caitlin McArthur. 2020. Transforming the Provision of Physiotherapy in the Time of COVID-19: A Call to Action for Telerehabilitation.Google ScholarGoogle Scholar
  22. Daniel S Scholz, Sönke Rhode, Michael Großbach, Jens Rollnik, and Eckart Altenmüller. 2015. Moving with music for stroke rehabilitation: a sonification feasibility study. Annals of the New York Academy of Sciences 1337, 1 (2015), 69–76.Google ScholarGoogle ScholarCross RefCross Ref
  23. Aneesha Singh, Nadia Bianchi-Berthouze, and Amanda CdeC Williams. 2017. Supporting everyday function in chronic pain using wearable technology. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 3903–3915.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Jessica Stanhope and Philip Weinstein. 2020. Learning from COVID-19 to improve access to physiotherapy. Australian Journal of Primary Health 26, 4 (2020), 271–272.Google ScholarGoogle ScholarCross RefCross Ref
  25. Richard Tang, Xing-Dong Yang, Scott Bateman, Joaquim Jorge, and Anthony Tang. 2015. Physio@ Home: Exploring visual guidance and feedback techniques for physiotherapy exercises. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 4123–4132.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Rick Tosti, John Jennings, and J Milo Sewards. 2013. Lateral epicondylitis of the elbow. The American journal of medicine 126, 4 (2013), 357–e1.Google ScholarGoogle Scholar
  27. Andrea Turolla, Giacomo Rossettini, Antonello Viceconti, Alvisa Palese, and Tommaso Geri. 2020. Musculoskeletal physical therapy during the COVID-19 pandemic: is telerehabilitation the answer?Physical therapy 100, 8 (2020), 1260–1264.Google ScholarGoogle Scholar
  28. Maarten A van Egmond, Raoul HH Engelbert, Jean HG Klinkenbijl, Mark I van Berge Henegouwen, and Marike van der Schaaf. 2020. Physiotherapy With Telerehabilitation in Patients With Complicated Postoperative Recovery After Esophageal Cancer Surgery: Feasibility Study. Journal of Medical Internet Research 22, 6 (2020), e16056.Google ScholarGoogle ScholarCross RefCross Ref
  29. B Vicenzino. 2003. Lateral epicondylalgia: a musculoskeletal physiotherapy perspective. Manual therapy 8, 2 (2003), 66–79.Google ScholarGoogle Scholar
  30. Conrad Wall III. 2010. Application of vibrotactile feedback of body motion to improve rehabilitation in individuals with imbalance. Journal of neurologic physical therapy: JNPT 34, 2 (2010), 98.Google ScholarGoogle ScholarCross RefCross Ref
  31. Shen Ye. 2015. The science behind Force Touch and the Taptic Engine. https://www.imore.com/science-behind-taptics-and-force-touchGoogle ScholarGoogle Scholar

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      • Published in

        cover image ACM Conferences
        CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
        May 2021
        2965 pages
        ISBN:9781450380959
        DOI:10.1145/3411763

        Copyright © 2021 ACM

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        Publication History

        • Published: 8 May 2021

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