A Methodology for Developing and Evaluating FBG-Based Smart 3D-Printed Prosthetics

Abstract

Lower limb amputation can greatly impact mobility and overall well-being. While recent advancements in 3D printing offer affordable and customizable prosthetics, maintaining structural integrity, performance, and accurate pressure measurements is essential. This study explores the use of Fiber Bragg Grating (FBG) sensors in 3D-printed prosthetics for real-time deformation monitoring. After modeling the prosthetic, Finite Element Analysis (FEA) was used to identify critical stress areas. These areas were then segmented and modeled, including a U-shaped segment for the metatarsal region and two linear segments at varying depths (0.4mm and 0.8mm). Our results show that the 0.8mm deep sensor demonstrated superior weight tolerance and response consistency compared to the 0.4mm deep sensor. This depth enabled more effective strain monitoring, enhancing response, recovery, and the reliability of the prosthetic. As for the U-shaped segments, both horizontally and vertically positioned sensors displayed rapid recovery and could bear maximum weight before reaching potential failure points.

Keywords: 3D Printing, Fiber Bragg Grating (FBG) Sensors, Strain Monitoring, Deformation Sensing, Finite Element Analysis (FEA)