Researchers at the Technion Viterbi Faculty of Electrical Engineering have developed a device that can diagnose neurological disease by tracking eyelid motion. The eyelid motion monitor technology (EMM) was tested on 100 healthy subjects to collect a base line of blinking patterns. This was then used to diagnose individuals with blepharospasm dystonia, a disease characterised by involuntary contraction of the muscles responsible for closing the eyes.
The hope is that this technology will be used in regular eye tests to diagnose all diseases that a expressed neurologically. The researchers are testing the technology in the diagnosis of dementia and Parkinson’s and hope to develop to cover Thyroid eye disease, Ptosis and other cranial nerve palsy.
What Do Your Eyes Say? Device Can Diagnose Diseases Based on Eyelid Motion
HAIFA, ISRAEL (October 15, 2017) – Researchers at the Technion-Israel Institute of Technology Viterbi Faculty of Electrical Engineering have developed a device that can diagnose diseases by means of an eyelid motion monitor (EMM). The project was published recently in Graefe’s Archive for Clinical and Experimental Ophthalmology.
Already in its developmental stages, the device has won several international awards, and was ranked in the top 20 in the Texas Instruments Innovation Challenge (TIIC) – Europe Design Contest. Over the past two years, the device has been used in clinical trials at Haemek Medical Center in Afula, Israel.
The device was first developed by Technion Prof. Levi Schachter and doctoral student Adi Hanuka, who began working on it as an undergraduate. Hanuka continued working on it during her graduate studies, with the help of a team of students working under her supervision.
“Eyelid motion provides us with meaningful information about the health of a patient,” explained Hanuka. “This motion can indicate not only eye diseases, but also neurological diseases such as Parkinson’s, and autoimmune diseases such as Grave’s. We developed a device that can be installed on the standard refraction glasses used in eye tests, at the request of Dr. Daniel Briscoe, Chairman of the Haemek Medical Center Department of Ophthalmology.”
Glasses are fitted with a hardware and software system that monitors and interprets eyelid movements. With approval of the Ethics Committee Regulations for Research Work Involving Human Participants, measurements of approximately 100 subjects have been collected in order to define the eyelid motion patterns (blinking speed and frequency) of a healthy person. Eyelid motions were analyzed using a signal-processing algorithm written by students Tal Berkowitz, Michal Spector, Shir Laufer, and Naama Pearl.
The team first examined blepharospasm dystonia, a disease characterized by involuntary contraction of the muscles responsible for closing the eyes. The researchers found a statistically significant quantitative relationship between a person’s eyelid pattern and the disease, which means that the device could be used to diagnose it. The system was also used to examine the effect of Botox injections, the conventional treatment for the disease, and it was found that within 15 minutes contractions decrease and the blinking pattern begins to match indices that exist among healthy people.
The researchers are also gathering information about other groups, including patients with dementia and Parkinson’s disease.
“Along with designing the product for purposes of commercialization, we are working in several directions: developing the device as a platform for multidisciplinary research on various topics such as the effect of emotions on blinking patterns; eyelid communication amongst the paralyzed; and automatic diagnosis through machine learning and based on a computerized comparison between the specific monitoring and an extensive database,” said Hanuka.
According to the researchers, the device has the potential to diagnose every disease that is expressed neurologically, including many ocular and systemic such as Ptosis, Thyroid eye disease, Parkinson’s disease, Myasthenia Gravis, and neurologic diseases such as third and seventh cranial nerve palsy.
Graph (CORR): Blinking speed as a function of the amplitude of motion. Green – a patient with blepharospasm dystonia blinking at very high speed.