This work focuses on optimizing the mechanical and electromechanical properties of a 3D-printed strain-sensing prosthetic socket fabricated using a conductive PETG-based composite (P15LT35 G) via Fused Deposition Modelling (FDM). A full factorial design (3 3 ) was implemented to study the influence of nozzle diameter (0.4, 0.5, 0.6 mm), infill pattern (grid, lines, gyroid), and infill density (30%, 50%, 70%) on performance characteristics. The socket was evaluated through tensile, flexural, impact, and compression testing, with the best configuration (0.4 mm nozzle, grid pattern, 70% infill) yielding a peak compressive strength of 25.62 MPa and a flexural strength of 31.72 MPa. Electrical characterization revealed that the optimized sensor exhibited a gauge factor of 1.52 with a nonlinearity coefficient of 4.01 under cyclic loading, indicating stable piezoresistive behavior. The low sensitivity, denoting controlled resistance changes under uniform loading, enhances signal reliability for limb-socket interface monitoring. ANOVA and Response Surface Methodology (RSM) were used to develop predictive models with high significance ( p < .05) and adjusted R 2 values exceeding 95%. The final prosthetic socket design includes embedded sensor paths and ventilation zones, validated through load simulations and experimental tests. The study demonstrates a robust approach for integrating sensing capability within structural components, offering a scalable solution for smart prosthetic systems.
Raj et al. (Fri,) studied this question.
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