Development and Testing of a Lightweight, All-Day Head-Mounted Wearable: Investigating the Visual Environment in Children for Myopia Risk Assessment

In recent years, the prevalence of myopia, caused by elongation of the eye, has increased dramatically. Researchers suggest that both light intensity and the range of viewing distances may influence myopia risk in children, but this remains unconfirmed. Investigating these environmental factors is therefore essential. While wearable devices have been used to gather relevant data, they often fall short, failing to measure spectral light content, estimate viewing distances across the central and near-peripheral visual field, or collect data at eye level. Previously, a research group developed an inexpensive, head-mounted sensor rig that safely captured relevant data from children during everyday activities. It measured spectral illumination and viewing distance variations across a wide central field, at the level of the child’s eyes. A pilot study confirmed the data's value, but limitations remained: the device’s size and weight could alter natural behavior, and its short recording duration restricted broader use. In this thesis a refined version, MYRA-TECH - MYopia Risk Assessment TECHnologies, is developed: a lightweight, head-mounted system designed to improve comfort, usability, and recording duration. The new design reduces movement constraints and simplifies use for both children and caregivers. It integrates an ESP32-S3 microcontroller, providing a strong balance of computing power and energy efficiency, supporting full-day data collection. All electronics are secured on the head and connect via a single cable to a small power bank worn on the back. The system captures two key parameters: object distance (combining monocular depth estimation and an 8x8 time of flight sensor) and ambient illuminance (via a spectral sensor). OV2640 DVP camera and VL53L5CX ToF sensor enable depth estimation, while the AS7341 spectral sensor measures light spectrum and intensity. An MPU6050 6-axis accelerometer supports activity recognition using machine learning, distinguishing behaviors such as reading, screen use, and outdoor play. The form factor ensures sensor alignment with the child’s eyes. Initial tests with five adults and one child evaluate performance, comfort, and data quality. MYRA-TECH enables the collection of statistical data on the everyday visual experiences of a child’s eyes, allowing researchers to explore potential correlations with myopia progression, offering a unique tool for long-term environmental monitoring in both research and clinical contexts.