Ocular administers a 20 minute visuospatial working memory task. For each trial, a patient is presented with 3 dot arrays, followed by a distractor image and probe. This serves as a mechanism to assess attentional performance.
In realtime, Ocular sends images of a patient's pupil through an optimized convolutional neural network (CNN) to detect the iris, produce a segmentation map of the pupil, and perform semantic segmentation, resulting in precise biometrics.
Biometric data is sent to a backend server and inputted into an optimized machine learning algorithm to analyze the millions of entries of time-series data.
A detailed summary of pupil dynamics is presented, along with biometrics and a probability of having ADHD. Moreover, an intelligent AI-based system outputs future steps for patients to take — whether a patient should see a neurologist, consult a medical practitioner, or seek immediate attention.