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Preliminary characterization of rectification for transradial prosthetic sockets
Calvin C Ngan1,2, Vishal Pendse1,2, Harry Sivasambu2
1University of Toronto, Toronto, Canada.
Scientific Reports
|March 8, 2024
Summary
This study characterizes transradial prosthetic socket design, identifying key modification zones and directions. Findings support a data-driven approach for more consistent and predictable prosthetic socket development.
Area of Science:
- Prosthetics and Orthotics
- Biomedical Engineering
- Rehabilitation Science
Background:
- Effective prosthesis use relies on accurate socket fit, yet digital socket design lacks standardization and has a steep learning curve.
- Existing research on digital socket design primarily targets lower-limb prostheses, leaving a gap in upper-limb applications.
- The transradial socket design process, particularly for the Northwestern-style socket, requires further characterization for improved systematic approaches.
Purpose of the Study:
- To characterize the design (rectification) process for the three-quarter Northwestern-style transradial socket.
- To lay the groundwork for a more systematic, data-driven approach to upper-limb prosthetic socket design.
- To identify common modification zones and quantify shape changes during socket rectification.
Main Methods:
- Comparison of 14 pairs of unrectified and rectified plaster models of transradial sockets.
- Shape analysis to identify common rectification zones.
- Novel 3D vector mapping technique to analyze shape changes in anterior-posterior and proximal-distal directions.
Main Results:
- Six common rectification zones were identified, with plaster addition being most significant in volume and surface area.
- 3D vector mapping revealed that shape modifications predominantly occurred in the anterior-posterior and proximal-distal directions.
- Consistent interquartile ranges for volume, surface deviation, and 3D vector representation across rectification zones were observed.
Conclusions:
- Initial findings suggest the potential for quantitative modeling of the transradial socket design process.
- This research opens possibilities for developing tools to categorize and predict socket designs using machine learning.
- Further development could lead to more standardized and predictable prosthetic socket design, benefiting a wider range of patients.

