Design and Development of a GUI-Based Remote Limb Measurement Platform and COMSOL- Assisted Material Analysis for Affordable Lightweight Transradial Prosthetic Arms

Abstract

Background: Normal transradial prosthetic fabrication involves regular clinical visits for anthropometric measures and customization, which prolongs the rehabilitation process and contributes to higher rehabilitation expenses. Furthermore, it is difficult to select lightweight materials with adequate mechanical strength for prosthetic fabrication. Objective: This study was designed to create and test a Graphical User Interface (GUI) based system for remotely measuring the length of a limb and to determine the best material for lightweight transradial prosthetic arms through the use of finite element analysis performed in COMSOL. Methods: An applied engineering design approach was adopted and consisted of two phases. In Phase I, a graphical user interface (GUI) was created in Python with the help of MediaPipe, OpenCV, CVzone, and NumPy Libraries, along with the Kivy application to estimate hand and arm dimensions from a distance. The system was tested with 23 subjects: 10 subjects with unilateral transradial amputation and 13 healthy subjects. In Phase II, three candidate materials (PLA, PETG and Polysulphone) were tested with COMSOL Multiphysics.  Results: The developed GUI achieved an average measurement accuracy of 94.91% in healthy participants and 98.23% in participants with unilateral transradial amputation, with a maximum measurement error below 2.1%. The simulation results showed that the Polysulphone material has the highest thermal stability, excellent stress resistance and lowest structural deformation of the material tested. PETG demonstrated good structural properties, while PLA was appropriate for lightweight, non-load-bearing parts. Conclusion: The proposed framework is efficient and works well when combining remote anthropometric measurement with simulation-based material optimization in order to develop a transradial prosthetic arm that is more affordable, lightweight and customizable. The study proves the feasibility of a computer vision-assisted Finite Element Analysis (FEA) system to improve prosthetic design, minimize clinical dependency and enable tele-rehabilitation applications.