MECHATRONIC SYSTEM DESIGN OF A LOW-COST NEAR-INFRARED VEIN VISUALIZATION PLATFORM BASED ON OPTOELECTRONIC INTEGRATION

Near-infrared (NIR) imaging systems have demonstrated significant potential for enhancing subcutaneous visualization applications; however, existing solutions are typically based on proprietary architectures with limited accessibility for experimental and engineering development. This work presents the mechanical and mechatronic design of a low-cost NIR vein visualization platform focused on optoelectronic integration, structural stability, and real-time image acquisition performance. The proposed system combines a controlled NIR illumination module, an infrared-sensitive imaging unit, and a compact processing architecture designed to operate under constrained computational resources while maintaining consistent visualization conditions. The mechanical structure was developed to ensure fixed spatial alignment between illumination and sensing components, minimizing optical noise and shadow artifacts through controlled geometry and working distance optimization. Image processing routines based on grayscale conversion and contrast enhancement were implemented to improve signal differentiation between vascular and surrounding tissue structures while preserving real-time operation capability. The modular architecture enables rapid prototyping, component scalability, and reproducibility using commercially available hardware elements. Experimental functional evaluation demonstrated stable visualization of superficial vascular patterns under controlled conditions, confirming adequate optical response and system repeatability for continuous operation scenarios. Compared with commercially available systems, the proposed platform significantly reduces implementation cost while preserving essential functional performance required for optoelectronic sensing applications. The presented design highlights the potential of low-cost mechatronic integration for developing scalable optical sensing platforms, providing a foundation for future improvements involving automated calibration, advanced image processing, and adaptive control strategies in electromechatronic systems.