Myopia is a leading cause of visual impairment worldwide, with prevalence rising rapidly among children. Growing evidence suggests that environmental and behavioral factors play a dominant role in ocular growth; however, current studies typically isolate single components of the visual environment, such as near work or light intensity, limiting investigators' understanding of how multiple visual stimuli interact within individuals over time. The retina is continuously exposed to a dynamic "visual diet," encompassing viewing distance, illuminance, spectral composition of light, and temporal viewing patterns, as well as associated visuomotor responses such as eye vergence and pupil dynamics. A critical barrier to myopia prevention is the lack of longitudinal, quantitative measurements that integrate these factors in real-world settings during childhood ocular development. The long-term goal of this project is to prevent myopia onset and slow myopia progression through individualized, patient-centered monitoring and modification of the visual diet. The overall objective of this proposal is to longitudinally characterize visual diet and visuomotor behavior in children and to identify the most influential environmental and physiological factors driving myopia onset and progression. The investigators will conduct a 3-year longitudinal observational study enrolling 60 children aged 7-12 years, including myopic children and non-myopic children stratified by risk of myopia progression.
Visual stimulation plays a critical role in guiding eye growth through activity dependent mechanisms. To date, this visual stimulation or visual diet has been investigated by measuring isolated components including near work, light intensity, or wavelength across different individuals. However, this approach does not address how multiple components of the visual diet interact in the visual development of each individual child. Knowledge gap: There is an urgent need for longitudinal measurements from individual children that incorporate multiple components of the visual environment and visual function as the eye grows and develops. This proposal addresses this gap by measuring longitudinally children's visual diet using a combination of techniques that will record these multiple components with VEET (Visual Environment Evaluation Tool, Meta Reality labs), modern eye tracking, refraction, and biometry. The understanding of the interactions between the visual environment and visual function will allow us to develop more effective approaches for myopia prevention and control. One major reason that visual diets remain under-investigated is the lack of appropriate technology. The investigators propose to use the novel VEET to measure spectral irradiance, illuminance, viewing distance, and head motion. In addition, the investigators propose to use modern wearable eye tracking to quantify visuomotor response during reading. The investigators' long-term goal is to prevent myopia onset and slow myopia progression in children through an individualized, patient-centered approach that monitors and modifies the visual diet. The specific objective of this proposal is to identify what individual features of the visual diet have the strongest impact on myopia development, and provide specific guidelines to monitor and modify them accordingly in an individualized manner.
Study Type
OBSERVATIONAL
Enrollment
60
SUNY College of Optometry
New York, New York, United States
RECRUITINGRefractive error (D)
Measured with an autorefractor
Time frame: From enrollment to the end of the 3-year study, every 6 months
Axial length (mm)
Measured with a biometer
Time frame: From enrollment to the end of the 3-year study, every 6 months
Viewing distance (cm)
Measured using the Visual Environment Evaluation Tool (VEET). VEET contains multiple time-of-flight (ToF) infrared sensors embedded in the temple arms of the glasses.The sensors emit infrared light toward objects in front of the wearer. The device measures the time required for the reflected infrared light to return to the sensor. Using the speed of light, the system calculates the distance between the eye/glasses and the viewed object.
Time frame: From enrollment to the end of the 3-year study, every 6 months
Illuminance (lux)
Measured with the Visual Environment Evaluation Tool (VEET). VEET uses photometric light sensors that detect the light intensity. The sensors convert incoming light into electrical signals proportional to brightness, and the device reports illuminance in lux, the standard unit for light exposure.
Time frame: From enrollment to the end of the 3-year study, every 6 months
Wavelength of the environmental light (nm)
Measured with the Visual Environment Evaluation Tool (VEET). The VEET measures light wavelength using integrated spectral light sensors that analyze the composition of incoming light across different portions of the visible spectrum. Rather than only measuring brightness (illuminance), the device also characterizes the spectral distribution of light reaching the wearer.
Time frame: From enrollment to the end of the 3-year study, every 6 months
Eye vergence (degree)
Using an eye tracker (Pupil Labs). Pupil Labs eye trackers measure eye vergence by tracking the gaze direction of both eyes separately and then calculating the angle between the two visual axes. Vergence refers to the inward or outward rotation of the eyes when focusing at different viewing distances: Convergence → eyes rotate inward for near targets Divergence → eyes rotate outward for distant targets Pupil Labs estimates vergence using these steps: 1. Track each eye independently 2. Estimate each eye's gaze vector in 3D 3. Compute where the two gaze vectors intersect 4. Calculate the vergence angle between them
Time frame: From enrollment to the end of the 3-year study, every 6 months
Pupil size (mm)
Using an eye tracker (Pupil Labs). Eye trackers measure pupil size using infrared video imaging and computer vision algorithms that detect the pupil boundary in images captured by eye-facing cameras. The eye tracker shines infrared (IR) light onto the eye using tiny IR LEDs. Infrared light is invisible to the user and produces stable illumination conditions for imaging the pupil. Small cameras pointed at the eyes continuously record high-speed grayscale images of the eye. The pupil appears darker than surrounding structures when using the "dark pupil" technique commonly used in wearable eye trackers. Finally, computer vision algorithms analyze each frame to locate the pupil region, identify the pupil edge, and fit a geometric shape to detect the pupil size in mm.
Time frame: From enrollment to the end of the 3-year study, every 6 months
Height (cm)
Using a stadiometer.
Time frame: From enrollment to the end of the 3-year study, every 6 months
Arm length (cm)
Measured using a tape measure.
Time frame: From enrollment to the end of the 3-year study, every 6 months
Accommodative facility
Using +/- 2.00 D flippers
Time frame: From enrollment to the end of the 3-year study, every 6 months
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.