Merging 3D Models of Two Public Domain Prosthetic Hands to Optimize Dexterity and Computer Control
Location
Poster #18
Start Date
1-5-2026 10:00 AM
Department
Other
Abstract
Additive manufacturing (3D printing) enables expedited prototyping and customization of prosthetic devices, making it an ideal platform for functional and personalized assistive technology. For this project, publicly available 3D models were sourced from Thingiverse, including dexterous finger designs and a motor-compatible palm and forearm structure. The models were imported into Tinkercad, where extensive redesign of their geometry was performed to ensure mechanical and structural compatibility. Modifications included proportional scaling of components, joint redesign to improve articulation, integration of internal tendon-routing channels, and custom servo mounting brackets. The final design uses a tendon-driven actuation system in which high-tension strings run through enclosed channels within the digits and palm. One servomotor independently actuates the thumb, while a second servo drives the four remaining fingers simultaneously, balancing mechanical simplicity with functional grasp capability. Fabrication was completed using a Stratasys SE dual-filament 3D printer. The printer’s soluble support material allowed for the creation of complex internal geometries, including enclosed tubing necessary for smooth tendon routing, which was then put through post processing via the dissolvement of the internal support filament, which would not be feasible with single-extrusion systems. The prosthetic will be controlled using an Arduino Nano microcontroller paired with integrated sensors to regulate motion and force output. Programmed control algorithms will coordinate servo movement, enabling repeatable grip patterns and adjustable actuation strength which can accurately mimic the articulation or a real human hand. To quantitatively evaluate dexterity, we plan to measure grip strength and the ability to manipulate standardized objects of varying size and shape. We believe that these metrics will help us to demonstrate the tangible results of our research efforts.
Faculty Sponsor
Charles Abrams
Merging 3D Models of Two Public Domain Prosthetic Hands to Optimize Dexterity and Computer Control
Poster #18
Additive manufacturing (3D printing) enables expedited prototyping and customization of prosthetic devices, making it an ideal platform for functional and personalized assistive technology. For this project, publicly available 3D models were sourced from Thingiverse, including dexterous finger designs and a motor-compatible palm and forearm structure. The models were imported into Tinkercad, where extensive redesign of their geometry was performed to ensure mechanical and structural compatibility. Modifications included proportional scaling of components, joint redesign to improve articulation, integration of internal tendon-routing channels, and custom servo mounting brackets. The final design uses a tendon-driven actuation system in which high-tension strings run through enclosed channels within the digits and palm. One servomotor independently actuates the thumb, while a second servo drives the four remaining fingers simultaneously, balancing mechanical simplicity with functional grasp capability. Fabrication was completed using a Stratasys SE dual-filament 3D printer. The printer’s soluble support material allowed for the creation of complex internal geometries, including enclosed tubing necessary for smooth tendon routing, which was then put through post processing via the dissolvement of the internal support filament, which would not be feasible with single-extrusion systems. The prosthetic will be controlled using an Arduino Nano microcontroller paired with integrated sensors to regulate motion and force output. Programmed control algorithms will coordinate servo movement, enabling repeatable grip patterns and adjustable actuation strength which can accurately mimic the articulation or a real human hand. To quantitatively evaluate dexterity, we plan to measure grip strength and the ability to manipulate standardized objects of varying size and shape. We believe that these metrics will help us to demonstrate the tangible results of our research efforts.