Team Gleason is excited to announce Project Insight, the creation of an open dataset of facial imagery of people living with ALS, to help advance innovation in computer vision and broaden the input potential for connectivity and communication.
Existing computer vision and machine learning datasets do not represent the diversity of people with ALS. This results in issues with the accuracy of identifying breathing masks, ptosis (droopy eyelids), epiphora (watery eyes), and dry eyes due to medications that control sialorrhea (excessive saliva).
Team Gleason is investigating the use of diverse data with AI and the front-facing camera already present in most computing devices to predict where a person is looking on a screen. In this Project Insight, Team Gleason is partnering with the Microsoft Health Next Enable team to gather images of people with ALS looking at their computer so that AI models can be trained inclusively.
Participants will be asked a brief medical history questionnaire and will be prompted through an app to submit images of them using their computer. An estimated 5 TB of anonymized data will be collected by Team Gleason and shared with researchers in data science collectives like Kaggle and GitHub.
“ALS progression can be as diverse as the individuals themselves,” explained Blair Casey, Team Gleason’s Chief Impact Officer. “So accessing computers and communication devices should not be a one size fits all,” Casey added. “We will capture as much information as possible from 100 people living with ALS, so we can develop tools for all to effectively use.”
