# From Mechanical Instability to Virtual Precision: Digital Twin Validation for Next-Generation MEMS-Based Eye-Tracking Systems

## TL;DR

The paper introduces a digital twin for MEMS-based eye trackers, enabling faster and more precise development of medical diagnostic tools.

## Contribution

A validated methodology for using digital twins to optimize MEMS-based optical systems is established.

## Key findings

- The digital twin accurately replicates physical system behavior with <30 µm geometric discrepancy.
- The DT-based pupil detection algorithm achieved 1.80 arc minute accuracy, outperforming commercial systems.

## Abstract

What are the main findings?

Digital twin of a real-life MEMS-based eye tracker.

Methodology for developing and verifying digital twins for opto-mechatronic systems.

What is the implication of the main finding?

Real-time 3D development platforms (like Unity) can be used to develop digital twins.

Ability to rapidly prototype and optimize in silico systems.

The development of high-performance MEMS-based eye trackers, crucial for next-generation medical diagnostics and human–computer interfaces, is often hampered by the mechanical instability and time-consuming recalibration of physical prototypes. To address this bottleneck, we present the development and rigorous validation of a high-fidelity digital twin (DT) designed to accelerate the design–test–refine cycle. We conducted a comparative study of a physical MEMS scanning system and its corresponding digital twin using a USAF 1951 test target under both static and dynamic conditions. Our analysis reveals that the DT accurately replicates the physical system’s behavior, showing a geometric discrepancy of <30 µm and a matching feature shift (1 µm error) caused by tracking dynamics. Crucially, the DT effectively removes mechanical vibration artifacts, enabling the precise analysis of system parameters in a controlled virtual environment. The validated model was then used to develop a pupil detection algorithm that achieved an accuracy of 1.80 arc minutes, a result that surpasses the performance of a widely used commercial system in our comparative tests. This work establishes a validated methodology for using digital twins in the rapid prototyping and optimization of complex optical systems, paving the way for faster development of critical healthcare technologies.