Wearable multi-color RAPD screening device

In this work, we developed a wearable, head-mounted device that automatically calculates the precise Relative Afferent Pupillary Defect (RAPD) value of a patient. The device consists of two RGB LEDs, two infrared cameras, and one microcontroller. In the RAPD test, the parameters like LED on-off durations, brightness level, and color of the light can be controlled by the user. Upon data acquisition, a computational unit processes the data, calculates the RAPD score and visualizes the test results with a user-friendly interface.Multiprocessing methods used on GUI to optimize the processing pipeline. We have shown that our head-worn instrument is easy to use, fast, and suitable for early-diagnostics and screening purposes for various neurological conditions such as RAPD, glaucoma, asymmetric glaucoma, and anisocoria.

Dynamic accommodation measurement using Purkinje reflections and ML algorithms

We developed a prototype device for dynamic gaze and accommodation measurements based on 4 Purkinje reflections (PR) suitable for use in AR and ophthalmology applications. PR1&2 and PR3&4 are used for accurate gaze and accommodation measurements, respectively. Our eye model was developed in ZEMAX and matches the experiments well. Our model predicts the accommodation from 4 diopters to 1 diopter with better than 0.25D accuracy. We performed repeatability tests and obtained accurate gaze and accommodation estimations from subjects. We are generating a large synthetic data set using physically accurate models and machine learning.

Artificial Eye Model and Holographic Display Based IOL Simulator

Cataract is a common ophthalmic disease in which a cloudy area is formed in the lens of the eye and requires surgical removal and replacement of eye lens. Careful selection of the intraocular lens (IOL) is critical for the post-surgery satisfaction of the patient. Although there are various types of IOLs in the market with different properties, it is challenging for the patient to imagine how they will perceive the world after the surgery. We propose a novel holographic vision simulator which utilizes non-cataractous regions on eye lens to allow the cataract patients to experience post-operative visual acuity before surgery. Computer generated holography display technology enables to shape and street the light beam through the relatively clear areas of the patient's lens. Another challenge for cataract surgeries is to match the right patient with the right IOL. To evaluate various IOLs, we developed an artificial human eye composed of a scleral lens, a glass retina, an iris, and a replaceable IOL holder. Next, we tested different IOLs (monofocal and multifocal) by capturing real-world scenes to demonstrate visual artifacts. Then, the artificial eye was implemented in the benchtop holographic simulator to evaluate various IOLs using different light sources and holographic contents.