The evaluation of the pupillary light response using pupillometry allows for an objective assessment of photoreceptor health in retinal and optic nerve conditions. Our team at the Singapore Eye Research Institute (SERI) has developed an affordable and easy-to-use handheld chromatic pupillometer (HCP) that relies on contemporary findings in retinal photoreception and machine learning, to allow a fast (1 min), affordable, and accurate detection of ocular diseases. The HCP has recently shown excellent performances for the detection of glaucoma (even in the presence of high myopia), diabetic retinopathy, and retinal dystrophies in a clinical setting. In this project, we will evaluate the usability and efficacy of HCP for the detection of ocular diseases in a community setting.

PhD Student and Research Fellow Positions are Available