The eyelids have it: Diagnosing disease by examining blinking
An innovative system for diagnosis of diseases based on eyelid movement was developed at the Viterbi Faculty of Electrical Engineering at Haifa’s Technion-Israel Institute of Technology. In the past two years, the device has been used in clinical trials at the Emek Medical Center in Afula.
The first scientific publication for the Afapayim (Eyelids) project was recently presented in the journal Graefe’s Archive for Clinical and Experimental Ophthalmology of the Springer Group.
The unique project was developed by Prof. Levi Schechter and doctoral student Adi Hanuka, who began working on it for her bachelor’s degree. She then continued with the help of many student groups which worked under her supervision. It has already won several international awards and was ranked in the top 20 places in the Texas Instruments International Competition.
The technology is relatively simple because it does not require a camera, image processing or storing data in a “cloud.”
“Eyelid movements provide significant information about the patient’s health,” explained Hanuka, who is currently doing a doctorate in another field, under Schechter’s guidance, on particle accelerators for medical purposes, such as radiotherapy in the treatment of cancerous tumors. “These movements can point not only to eye diseases but also to neurological diseases, such as Parkinson’s disease and autoimmune diseases such as Graves’ disease [hyperthyroidism]. At the request of Dr. Daniel Brisko, chief of ophthalmology at Emek, we developed a device that is fitted with standard optometrist glasses used in eye examinations.”
The glasses are fitted with a system of hardware and software that monitors the user’s eyelid movements and decodes them. Since the approval of the Helsinki Committee for Human Experimentation, measurements of approximately 100 subjects have been collected to define the patterns of blinking (frequency and speed of closure) in a healthy person.
The analysis of the eyelid indices was carried out using a signal-processing algorithm written by four students in the faculty – Tal Berkowitz, Michal Spector, Shir Laufer and Naama Pearl.
The first disease to be diagnosed was blepharospasm dystonia, characterized by an involuntary contraction of the muscles responsible for closing the eyes. The researchers found a significant quantitative association between the person’s eyelid pattern and suffering from spasms of the eyelids.
The system also examined the effect of the usual treatment of the disease, Botox injection, and found that within 15 minutes of the injection, the contractions were alleviated and the eyelid movement pattern normalizes.