Design and 3D printing of high-frequency micro-strip patch antenna-based pressure sensor for burn rehabilitation monitoring

Purpose This study aims to investigate the influence of substrate’s different infill patterns at 20% infill density of micro strip patch antenna (MPA) based sensor performance with a particular focus on the metrics such as radiofrequency (Rf) performance, insertion loss (S11) and specific absorption ratio (SAR) under both loaded and unloaded conditions. Design/methodology/approach Different 14 infill patterns of polylactic acid (PLA) substrates were fabricated using three-dimensional (3D) printing based on fused filament fabrication with 20% infill density. The Rf and S11 of the MPA pressure sensor sensitivity were experimentally evaluated using a vector network analyser setup by applying a loads of 5 N–25 N. The dielectric constant, Rf and S11 and SAR value were calculated for solid disk (100% infill density) and 20% infill density disk. In addition, mechanical and electromagnetic finite element modelling (FEM) simulations were conducted to correlate simulation with experimental results. Findings The grid pattern (20% infill density of PLA) exhibits the highest (approximately 139%) dielectric constant value of 9.0 and lesser (approximately 3.5 %) SAR value of 1.470 W/kg, while the solid PLA sample (100% infill density) shows the lowest dielectric constant value of 3.8 and higher 1.520 W/kg. Experimental testing demonstrated a resonance frequency shift from 4.31 GHz (No load), 4.35 GHz (5 N), 4.30 GHz (10 N), 4.27 GHz (15 N), 4.06 GHz (20 N), 3.87 GHz (under 25 N load), accompanied by a corresponding S11 change from −26.95 dB to −17.04 dB, confirming the sensor’s pressure sensitivity. Originality/value This study presents comprehensive analysis of 3D-printed infill patterns affecting the Rf, S11 and SAR values of MPA-based pressure sensors. The experimental validation with FEM modelling provides valuable insights for designing customizable and efficient wearable MPA-based pressure sensor using 3D printing technique suiting burn rehabilitation monitoring applications.