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At-Home Pupillometry using Smartphone Facial Identification Cameras
Colin Barry1, Jessica De Souza1, Yinan Xuan1
1Department of Electrical and Computer Engineering, University of California: San Diego La Jolla, California, USA.
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI Conference
|November 30, 2023
Summary
A new smartphone pupillometer offers accurate, at-home pupil dilation measurements for early disease detection. This accessible tool shows promise for remote clinical research, especially with older adults.
Area of Science:
- Biomedical Engineering
- Ophthalmology
- Medical Devices
Background:
- Pupillary response research is advancing in medical and psychiatric fields.
- Accessible pupillometers can aid in early neurological disease detection and cognitive load assessment.
- Current clinical research often lacks convenient, at-home pupil measurement tools.
Purpose of the Study:
- To introduce a novel smartphone-based pupillometer for at-home pupil measurements.
- To enable future clinical research and development in remote pupil monitoring.
- To assess the accuracy and usability of a smartphone pupillometer system.
Main Methods:
- Utilized a smartphone's NIR front-facing camera for facial recognition and RGB selfie camera for pupil tracking.
- Developed a system for tracking absolute pupil dilation with sub-millimeter accuracy.
- Compared the smartphone system against a gold standard pupillometer during a pupillary light reflex test.
Main Results:
- Achieved a median Mean Absolute Error (MAE) of 0.27mm for absolute pupil dilation tracking.
- Demonstrated a median error of 3.52% for pupil dilation change tracking.
- A remote usability study with older adults showed promising results for self-operation.
Conclusions:
- The smartphone-based pupillometer is a viable, accurate tool for at-home pupil measurements.
- The system holds significant potential for remote clinical research and data collection, particularly in diverse populations.
- This technology can broaden access to pupillary response analysis for medical and psychiatric applications.
