Mathematical Modeling and Data Science for Tear Breakup on the Ocular Surface

  • January 6, 2022 from 12:00-1:00pm
  • Virtual presentation via BlueJeans ( | Meeting ID 361095905
  • Please RSVP by emailing Debra Reese. Please include your full name, email address, and institution/organization.
  • This activity has been approved for AMA PRA Category 1 Credit. We will provide instructions on obtaining CME credit for attendance.

The tear film is a thin fluid multilayer left on the eye surface after a blink. A good tear film is essential for health and proper function of the eye, yet millions have a condition called dry eye disease (DED) that inhibits vision and may lead to inflammation and ocular surface damage.

There is little quantitative data about tear film failure, often called tear break up (TBU). Currently, it is not possible to directly measure important variables such as tear osmolarity with TBU.

We discuss automatic methods we have developed to extract data from video of healthy eyes, and to estimate important variables like osmolarity within regions of TBU. Not only is new data obtained, but far more data enabling statistical methods to be applied. So far, the methods provide baseline data for TBU in healthy subjects; future work will produce data from DED subjects.

Meet the Speaker

After a postdoc at National Institute of Standards and Technology, Dr. Braun started at the University of Delaware in the Department of Mathematical Sciences.  Since 2002, he has collaborated with mathematicians, engineers, optometrists and ophthalmologists on studying tear film dynamics and ocular surface.  Since then, he has supervised many award-winning students in this area, ranging from undergraduates to PhDs, with funding from NSF and NIH grants.  After becoming the founding director of UD’s MS in Data Science program, his research increasingly includes data science for understanding the ocular surface, in the hope of aiding diagnosis and treatment of conditions like dry eye.

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