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A Proposed Computer-Vision Based Upper-Limb Rehabilitation & Evaluation Suite

Published: 27 September 2023 Publication History

Abstract

Hand function impairment is a common consequence of stroke, requiring continuous monitoring and kinematic evaluations to assess motor recovery progress. The Sollerman Hand Function Test (SHT) and the Box and Block Test (BBT) are some essential assessment tools for evaluating patients’ ability to perform everyday activities. However, the need for physical presence of a therapist and the use of specialized materials makes the process time-consuming and dependent on the availability of clinical resources. This paper focuses on the development of a computer vision based upper-limb rehabilitation suite that includes virtual alternatives to traditional sub-tests found in the SHT, along with a digital version of the Box and Block Test, that do not require extra hardware equipment. Following a concise overview of existing research methodologies, we thoroughly examine and showcase our implemented solution while also addressing pertinent challenges and constraints. Finally, usability issues of the applications and necessary adjustments, are also discussed.

References

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Sungmin Cho, Won Seok Kim, Nam Jong Paik, and Hyunwoo Bang. 2016. Upper-Limb Function Assessment Using VBBTs for Stroke Patients. IEEE Computer Graphics and Applications 36, 1 (1 Jan. 2016), 70–78. https://doi.org/10.1109/MCG.2015.2 Publisher Copyright: © 1981-2012 IEEE.
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Catherine Coshall, Ruth Dundas, Judy Stewart, Anthony Rudd, Rachmond Howard, and Charles Wolfe. 2001. Estimates of the Prevalence of Acute Stroke Impairments and Disability in a Multiethnic Population. Stroke; a journal of cerebral circulation 32 (06 2001), 1279–84. https://doi.org/10.1161/01.STR.32.6.1279
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Chih-Pin Hsiao, Chen Zhao, and Ellen Do. 2013. The Digital Box and Block Test Automating traditional post-stroke rehabilitation assessment. 2013 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2013, 360–363. https://doi.org/10.1109/PerComW.2013.6529516
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Youn. K. Kim and Xiaoli Yang. 2006. Hand-writing Rehabilitation in the Haptic Virtual Environment. In 2006 IEEE International Workshop on Haptic Audio Visual Environments and their Applications (HAVE 2006). 161–164. https://doi.org/10.1109/HAVE.2006.283792
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Abhik Singla, Partha Pratim Roy, and Debi Prosad Dogra. 2019. Visual rendering of shapes on 2D display devices guided by hand gestures. Displays 57 (2019), 18–33. https://doi.org/10.1016/j.displa.2019.03.001
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Christer Sollerman and Arvid Ejeskär. 1995. Sollerman Hand Function Test: A Standardised Method and its Use in Tetraplegic Patients. Scandinavian Journal of Plastic and Reconstructive Surgery and Hand Surgery 29, 2 (1995), 167–176. https://doi.org/10.3109/02844319509034334 arXiv:https://doi.org/10.3109/02844319509034334PMID: 7569815.
[7]
Dimitrios Soumis, Orestis Zestas, Kyriakos Kyriakou, Kyriaki Seklou, and Nikolaos Tselikas. 2022. Digital Version of the “Open/Close Zip” Subtest included in the Sollerman Hand Function Test. 1–5. https://doi.org/10.1109/PACET56979.2022.9976369
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Li-Yao Weng, Ching-Lin Hsieh, Kwang-Yi Tung, Tzyy-Jiuan Wang, Yu-Chih Ou, Li-Ru Chen, Shiun-Lei Ban, Wei-Wei Chen, and Chin-Feng Liu. 2010. Excellent Reliability of the Sollerman Hand Function Test for Patients With Burned Hands. Journal of Burn Care & Research 31, 6 (11 2010), 904–910. https://doi.org/10.1097/BCR.0b013e3181f93583 arXiv:https://academic.oup.com/jbcr/article-pdf/31/6/904/22483684/01253092-201011000-00007.pdf
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Carolee Winstein, Joel Stein, Ross Arena, Barbara Bates, Leora Cherney, Steven Cramer, Frank Deruyter, Janice Eng, Beth Fisher, Richard Harvey, Catherine Lang, Marilyn MacKay-Lyons, Kenneth Ottenbacher, Sue Pugh, Mathew Reeves, Lorie Richards, William Stiers, and Rich Zorowitz. 2016. Guidelines for Adult Stroke Rehabilitation and Recovery: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association. Stroke 47 (05 2016), STR.0000000000000098. https://doi.org/10.1161/STR.0000000000000098
[10]
Orestis N. Zestas, Dimitrios N. Soumis, Kyriakos D. Kyriakou, Kyriaki Seklou, and Nikolaos D. Tselikas. 2022. The Computer Vision Box & Block Test in Rehabilitation Assessment. In 2022 Panhellenic Conference on Electronics & Telecommunications (PACET). 1–4. https://doi.org/10.1109/PACET56979.2022.9976370
[11]
Orestis N. Zestas, Dimitrios N. Soumis, Kyriakos D. Kyriakou, Kyriaki Seklou, and Nikolaos D. Tselikas. 2023. A computer-vision based hand rehabilitation assessment suite. AEU - International Journal of Electronics and Communications 169 (2023), 154762. https://doi.org/10.1016/j.aeue.2023.154762

Cited By

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  • (2024)A Smart-Glove Approach in Upper-limb Rehabilitation Assessment2024 Panhellenic Conference on Electronics & Telecommunications (PACET)10.1109/PACET60398.2024.10497059(1-4)Online publication date: 28-Mar-2024
  • (2024)Hand Function Assessment using Computer Vision for Hand Rehabilitation2024 IEEE Conference on Artificial Intelligence (CAI)10.1109/CAI59869.2024.00129(659-664)Online publication date: 25-Jun-2024
  • (2024)Realizing computer vision rehabilitation assessment tests & evaluation applications for mobile devicesAEU - International Journal of Electronics and Communications10.1016/j.aeue.2024.155473186(155473)Online publication date: Nov-2024

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cover image ACM Other conferences
CHIGREECE '23: Proceedings of the 2nd International Conference of the ACM Greek SIGCHI Chapter
September 2023
218 pages
ISBN:9798400708886
DOI:10.1145/3609987
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 September 2023

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Author Tags

  1. Box & Block Test
  2. Computer Vision
  3. Fine Motor Skills
  4. Rehabilitation Assessment
  5. Sollerman Hand Function Test
  6. Upper-limb Rehabilitation

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Cited By

View all
  • (2024)A Smart-Glove Approach in Upper-limb Rehabilitation Assessment2024 Panhellenic Conference on Electronics & Telecommunications (PACET)10.1109/PACET60398.2024.10497059(1-4)Online publication date: 28-Mar-2024
  • (2024)Hand Function Assessment using Computer Vision for Hand Rehabilitation2024 IEEE Conference on Artificial Intelligence (CAI)10.1109/CAI59869.2024.00129(659-664)Online publication date: 25-Jun-2024
  • (2024)Realizing computer vision rehabilitation assessment tests & evaluation applications for mobile devicesAEU - International Journal of Electronics and Communications10.1016/j.aeue.2024.155473186(155473)Online publication date: Nov-2024

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