Exploring the Potential of Generative AI in DIY Assistive Technology Design by Occupational Therapists
Article No.: 109, Pages 1 - 6
Abstract
This paper examines the potential integration of generative AI into the assistive technology (AT) making and adaptation process, with Occupational Therapists (OTs) as the primary beneficiaries, as they are often involved in designing ‘do-it-yourself assistive technology’ (DIY AT) to support independent living for individuals with disabilities. We initiated the study by considering the traditional AT-making processes performed by OTs and prototyped a web interface that incorporates generative AI to support these processes. Through a series of user studies, we collected OTs' preliminary insights on how generative AI could bridge the gap between clinical reasoning and technical design, potentially streamlining the AT creation and adaptation process while maintaining the crucial element of personalized AT solutions. The study's findings highlight several key benefits of generative AI in OT practice: 1) customization of AT solutions tailored to individual client needs, 2) improved visualization capabilities for client communication, 3) inspiration for new AT design ideas, and 4) potential for rapid prototyping and practice. However, key drawbacks were noted, including limitations in inputting measurements, which can lead to inaccurate outputs and necessitate substantial modifications to the created AT, along with challenges associated with the current state of generative AI.
References
[1]
L. Aflatoony and S. Kolarić. 2022. One Size Doesn't Fit All: On the Adaptable Universal Design of Assistive Technologies. Proceedings of the Design Society 2: 1209–1220. https://doi.org/10.1017/pds.2022.123
[2]
L. Aflatoony and S. J. Lee. 2020. CODEA: A FRAMEWORK FOR CO-DESIGNING ASSISTIVE TECHNOLOGIES WITH OCCUPATIONAL THERAPISTS, INDUSTRIAL DESIGNERS, AND END-USERS WITH MOBILITY IMPAIRMENTS. Proceedings of the Design Society: DESIGN Conference 1: 1843–1852. https://doi.org/10.1017/dsd.2020.332
[3]
Leila Aflatoony and Shreya Shenai. 2021. Unpacking the Challenges and Future of Assistive Technology Adaptation by Occupational Therapists. In CHItaly 2021: 14th Biannual Conference of the Italian SIGCHI Chapter, 1–8. https://doi.org/10.1145/3464385.3464715
[4]
Paul W. Brand and Anne M. Hollister. 1999. Clinical Mechanics of the Hand. Mosby.
[5]
Erin Buehler, Niara Comrie, Megan Hofmann, Samantha McDonald, and Amy Hurst. 2016. Investigating the Implications of 3D Printing in Special Education. ACM Transactions on Accessible Computing 8, 3: 1–28. https://doi.org/10.1145/2870640
[6]
Patrick A Carrington, Shannon Hosmer, Tom Yeh, Amy Hurst, and Shaun K Kane. 2015. “Like This, But Better”: Supporting Novices’ Design and Fabrication of 3D Models Using Existing Objects.
[7]
Xiang “Anthony” Chen, Jeeeun Kim, Jennifer Mankoff, Tovi Grossman, Stelian Coros, and Scott E. Hudson. 2016. Reprise: A Design Tool for Specifying, Generating, and Customizing 3D Printable Adaptations on Everyday Objects. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology, 29–39. https://doi.org/10.1145/2984511.2984512
[8]
Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, and Edward Raff. 2022. VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance. In Computer Vision – ECCV 2022, Shai Avidan, Gabriel Brostow, Moustapha Cissé, Giovanni Maria Farinella and Tal Hassner (eds.). Springer Nature Switzerland, Cham, 88–105. https://doi.org/10.1007/978-3-031-19836-6_6
[9]
Faraz Faruqi, Ahmed Katary, Tarik Hasic, Amira Abdel-Rahman, Nayeemur Rahman, Leandra Tejedor, Mackenzie Leake, Megan Hofmann, and Stefanie Mueller. 2023. Style2Fab: Functionality-Aware Segmentation for Fabricating Personalized 3D Models with Generative AI. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, 1–13. https://doi.org/10.1145/3586183.3606723
[10]
Wei Gao, Yunbo Zhang, Devarajan Ramanujan, Karthik Ramani, Yong Chen, Christopher B. Williams, Charlie C.L. Wang, Yung C. Shin, Song Zhang, and Pablo D. Zavattieri. 2015. The status, challenges, and future of additive manufacturing in engineering. Computer-Aided Design 69: 65–89. https://doi.org/10.1016/j.cad.2015.04.001
[11]
Erin Higgins, William Berkley Easley, Karen L. Gordes, Amy Hurst, and Foad Hamidi. 2022. Creating 3D Printed Assistive Technology Through Design Shortcuts: Leveraging Digital Fabrication Services to Incorporate 3D Printing into the Physical Therapy Classroom: Leveraging Digital Fabrication Services to Incorporate 3D Printing into the Physical Therapy Classroom. In Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility, 1–16. https://doi.org/10.1145/3517428.3544816
[12]
Megan Hofmann, Gabriella Hann, Scott E. Hudson, and Jennifer Mankoff. 2018. Greater than the Sum of its PARTs: Expressing and Reusing Design Intent in 3D Models. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1–12. https://doi.org/10.1145/3173574.3173875
[13]
Megan Hofmann, Kristin Williams, Toni Kaplan, Stephanie Valencia, Gabriella Hann, Scott E. Hudson, Jennifer Mankoff, and Patrick Carrington. 2019. “Occupational Therapy is Making”: Clinical Rapid Prototyping and Digital Fabrication. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–13. https://doi.org/10.1145/3290605.3300544
[14]
Megan Hunzeker and Rebecca Ozelie. 2021. A Cost-Effective Analysis of 3D Printing Applications in Occupational Therapy Practice. The Open Journal of Occupational Therapy 9, 1: 1–12. https://doi.org/10.15453/2168-6408.1751
[15]
Jeeeun Kim, Anhong Guo, Tom Yeh, Scott E. Hudson, and Jennifer Mankoff. 2017. Understanding Uncertainty in Measurement and Accommodating its Impact in 3D Modeling and Printing. In Proceedings of the 2017 Conference on Designing Interactive Systems, 1067–1078. https://doi.org/10.1145/3064663.3064690
[16]
Udaya Lakshmi, Megan Hofmann, Kelly Mack, Scott E. Hudson, Jennifer Mankoff, and Rosa I. Arriaga. 2021. Medical Maker Response to COVID-19: Distributed Manufacturing Infrastructure for Stopgap Protective Equipment. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 1–13. https://doi.org/10.1145/3411764.3445395
[17]
Udaya Lakshmi, Megan Hofmann, Stephanie Valencia, Lauren Wilcox, Jennifer Mankoff, and Rosa I. Arriaga. 2019. “Point-of-Care Manufacturing”: Maker Perspectives on Digital Fabrication in Medical Practice. Proceedings of the ACM on Human-Computer Interaction 3, CSCW: 1–23. https://doi.org/10.1145/3359193
[18]
Seung Won Lee, Tae Hee Jo, Semin Jin, Jiin Choi, Kyungwon Yun, Sergio Bromberg, Seonghoon Ban, and Kyung Hoon Hyun. 2024. The Impact of Sketch-guided vs. Prompt-guided 3D Generative AIs on the Design Exploration Process. In Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–18. https://doi.org/10.1145/3613904.3642218
[19]
Mixuan Li and Leila Aflatoony. 2023. A Parametric Design Tool to Support Customized Adaptations of Assistive Technologies for People with Hand Impairments. In The 25th International ACM SIGACCESS Conference on Computers and Accessibility, 1–4. https://doi.org/10.1145/3597638.3614492
[20]
Vivian Liu, Jo Vermeulen, George Fitzmaurice, and Justin Matejka. 2023. 3DALL-E: Integrating Text-to-Image AI in 3D Design Workflows. In Proceedings of the 2023 ACM Designing Interactive Systems Conference, 1955–1977. https://doi.org/10.1145/3563657.3596098
[21]
Kelly Avery Mack, Rida Qadri, Remi Denton, Shaun K. Kane, and Cynthia L. Bennett. 2024. “They only care to show us the wheelchair”: disability representation in text-to-image AI models. In Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–23. https://doi.org/10.1145/3613904.3642166
[22]
Jennifer Mankoff, Megan Hofmann, Xiang “Anthony” Chen, Scott E. Hudson, Amy Hurst, and Jeeeun Kim. 2019. Consumer-grade fabrication and its potential to revolutionize accessibility. Communications of the ACM 62, 10: 64–75. https://doi.org/10.1145/3339824
[23]
Samantha McDonald, Niara Comrie, Erin Buehler, Nicholas Carter, Braxton Dubin, Karen Gordes, Sandy McCombe-Waller, and Amy Hurst. 2016. Uncovering Challenges and Opportunities for 3D Printing Assistive Technology with Physical Therapists. In Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility, 131–139. https://doi.org/10.1145/2982142.2982162
[24]
Howard P Parette. 2024. Assistive Technology Devices and Services.
[25]
Winke Pont, Iris Groeneveld, Henk Arwert, Jorit Meesters, Radha Rambaran Mishre, Thea Vliet Vlieland, Paulien Goossens, and on behalf of the SCORE-study group. 2020. Caregiver burden after stroke: changes over time? Disability and Rehabilitation 42, 3: 360–367. https://doi.org/10.1080/09638288.2018.1499047
[26]
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi. Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.
[27]
Karin Slegers, Kristel Kouwenberg, Tereza Loučova, and Ramon Daniels. 2020. Makers in Healthcare: The Role of Occupational Therapists in the Design of DIY Assistive Technology. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–11. https://doi.org/10.1145/3313831.3376685
[28]
G J Snoek, M J IJzerman, H J Hermens, D Maxwell, and F Biering-Sorensen. 2004. Survey of the needs of patients with spinal cord injury: impact and priority for improvement in hand function in tetraplegics. Spinal Cord 42, 9: 526–532. https://doi.org/10.1038/sj.sc.3101638
[29]
Rune Thorsen, Denise Cugnod, Marina Ramella, Rosa Maria Converti, and Maurizio Ferrarin. 2024. From patient to maker - a workflow including people with cerebral palsy in co-creating assistive devices using 3D printing technologies. Disability and Rehabilitation: Assistive Technology 19, 4: 1358–1368. https://doi.org/10.1080/17483107.2023.2177754
[30]
Cesar Vandevelde, Francis Wyffels, Maria-Cristina Ciocci, Bram Vanderborght, and Jelle Saldien. 2016. Design and evaluation of a DIY construction system for educational robot kits. International Journal of Technology and Design Education 26, 4: 521–540. https://doi.org/10.1007/s10798-015-9324-1
[31]
Samangi Wadinambiarachchi, Ryan M. Kelly, Saumya Pareek, Qiushi Zhou, and Eduardo Velloso. 2024. The Effects of Generative AI on Design Fixation and Divergent Thinking. In Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–18. https://doi.org/10.1145/3613904.3642919
[32]
Yunlong Wang, Shuyuan Shen, and Brian Y Lim. 2023. RePrompt: Automatic Prompt Editing to Refine AI-Generative Art Towards Precise Expressions. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–29. https://doi.org/10.1145/3544548.3581402
[33]
Joshua Z. Zheng, Sara De La Rosa, and Aaron M. Dollar. 2011. An investigation of grasp type and frequency in daily household and machine shop tasks. In 2011 IEEE International Conference on Robotics and Automation, 4169–4175. https://doi.org/10.1109/ICRA.2011.5980366
[34]
2024. 3D AI Studio - Create Custom 3D Models with AI. Retrieved July 2, 2024 from https://www.3daistudio.com/
[35]
Midjourney. Midjourney. Retrieved July 2, 2024 from https://www.midjourney.com/website
Index Terms
- Exploring the Potential of Generative AI in DIY Assistive Technology Design by Occupational Therapists
Index terms have been assigned to the content through auto-classification.
Recommendations
DIY Assistive Software: End-User Programming for Personalized Assistive Technology
Existing assistive technologies often fail to support the unique and personalized needs of blind and visually impaired (BVI) people. Thus, BVI people have become domain experts in customizing and 'hacking' assistive technology in order to creatively suit ...
Hacking, Switching, Combining: Understanding and Supporting DIY Assistive Technology Design by Blind People
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing SystemsExisting assistive technologies (AT) often fail to support the unique needs of blind and visually impaired (BVI) people. Thus, BVI people have become domain experts in customizing and ‘hacking’ AT, creatively suiting their needs. We aim to understand ...
Unpacking the Challenges and Future of Assistive Technology Adaptation by Occupational Therapists
CHItaly '21: Proceedings of the 14th Biannual Conference of the Italian SIGCHI ChapterOccupational therapists (OTs) suggest or prescribe assistive technologies (AT) for use by a particular patient. OTs often need to modify, refine, or repurpose existing, off-the-shelf ATs in order to better address the specific health-related conditions, ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
October 2024
1475 pages
ISBN:9798400706776
DOI:10.1145/3663548
Copyright © 2024 Owner/Author.
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.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 October 2024
Check for updates
Qualifiers
- Poster
- Research
- Refereed limited
Conference
ASSETS '24
Sponsor:
ASSETS '24: The 26th International ACM SIGACCESS Conference on Computers and Accessibility
October 27 - 30, 2024
NL, St. John's, Canada
Acceptance Rates
Overall Acceptance Rate 436 of 1,556 submissions, 28%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 101Total Downloads
- Downloads (Last 12 months)101
- Downloads (Last 6 weeks)48
Reflects downloads up to 28 Dec 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format