Simulation of an Adaptive X-Ray Control Interface Using Automated Anthropometry and Thermal Motion Detection

2026-01-19T02:50:26+00:00

Manual determination of radiographic exposure parameters often results in inconsistent radiation dosing due to subjective assessment of patient body habitus. This study presents the design and component-level simulation of an automated control interface that regulates tube voltage (kV) and current-time (mAs) based on patient Body Mass Index (BMI). The system architecture integrates a sensor fusion array comprising a VL53L0X Time-of-Flight sensor for non-contact vertical ranging, a strain gauge load cell for gravimetric acquisition, and an AMG8833 thermal grid to enforce a stillness protocol before measurement. A central microcontroller processes these inputs using a combined linear and quadratic algorithm to derive optimal exposure settings, incorporating a variable correction factor for machine-specific characteristics. The control logic was validated through an electronic simulation of a capacitor discharge X-ray generator. Results demonstrate robust performance, with biometric acquisition achieving gravimetric accuracy exceeding 97% and absolute vertical precision. Furthermore, the simulated high-voltage control loop successfully mapped five distinct BMI categories to their corresponding target voltages (57kV–69kV) with a deviation of less than 2%. This research confirms the analytical feasibility of utilizing automated anthropometry to drive high-voltage circuitry, offering a technological pathway to reduce operator error and standardize radiation protection in diagnostic imaging.

SANITAS: Jurnal Teknologi dan Seni Kesehatan

Simulation of an Adaptive X-Ray Control Interface Using Automated Anthropometry and Thermal Motion Detection