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

Mateusz Pomianek¹, Marek Piszczek², Paweł Stawarz¹

¹Department of Computer and Control Engineering, Rzeszow University of Technology, Wincentego Pola 2, 35-021 Rzeszów, Poland.

Sensors (Basel, Switzerland)

|October 29, 2025

Summary

This summary is machine-generated.

This study introduces a high-fidelity digital twin (DT) to overcome challenges in developing MEMS eye trackers. The validated DT accurately simulates physical systems, enabling faster design cycles and improved pupil detection algorithms for medical diagnostics.

Keywords:

MEMS engineering digital twin gaze tracking hardware-in-the-loop real-time simulation virtual validation

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Last Updated: Jan 13, 2026

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Area of Science:

Optics and Photonics
Microelectromechanical Systems (MEMS)
Biomedical Engineering

Background:

MEMS-based eye trackers are vital for medical diagnostics and human-computer interfaces.
Physical prototype development faces limitations due to mechanical instability and recalibration needs.
Accelerating the design-test-refine cycle is critical for advancing eye-tracking technology.

Purpose of the Study:

To develop and validate a high-fidelity digital twin (DT) for MEMS eye trackers.
To accelerate the design-test-refine cycle for MEMS optical systems.
To demonstrate the DT's utility in developing advanced pupil detection algorithms.

Main Methods:

Comparative analysis of a physical MEMS scanning system and its digital twin using a USAF 1951 test target.
Evaluation under static and dynamic conditions to assess accuracy and identify discrepancies.
Utilizing the validated DT to develop and test a novel pupil detection algorithm.

Main Results:

The digital twin accurately replicated the physical system's behavior with <30 µm geometric discrepancy.
Tracking dynamics introduced a 1 µm error in feature shift, which the DT successfully modeled.
The DT eliminated mechanical vibration artifacts, allowing for precise parameter analysis.
A pupil detection algorithm developed using the DT achieved 1.80 arc minutes accuracy, outperforming a commercial system.

Conclusions:

A validated methodology for employing digital twins in rapid prototyping of optical systems has been established.
Digital twins offer a powerful tool for overcoming physical limitations in MEMS eye tracker development.
This approach accelerates the development of critical healthcare technologies, including advanced eye-tracking systems.