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

Abstract

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.