Why do we need pupil detection methods?

There is an upcoming trend of health smartphone apps that measure all kinds of personal data to provide insight into certain aspects of someone’s health. However, some health apps are a little bit more specialized towards a specific group of people. At Orikami, we develop digital biomarkers and implement them in a mobile app like MS Sherpa. MS Sherpa personalizes healthcare for people with multiple sclerosis (MS) and measures the patient’s mobility, cognitive function and fatigue over time. One of these aspects, fatigue, can be determined by the delay and the speed of an eye saccade after a certain visual stimuli (Finke et al. 2012). While the patient is performing the eye saccade task on their smartphone, the patient’s front-facing camera records the face. Before we are able to determine the delay and speed of the saccade from this recording, we first need to find the location of the patient’s pupil. This is where pupil detection methods come in, to help us find the center of the pupil.

In this post, I will introduce four pupil detection methods and compare them to each other on four different datasets.

Read more in at blogsite: Blog Anneloes Ernest – Orikami Blog