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The growth of research with active pupilometry

In recent decades, pupillometry has been useful for healthcare professionals. Initially, the method was limited to the use of a flashlight aimed at the pupil to assess the impairment of consciousness. Advances in technology and the development of devices capable of accurately measuring pupil diameter have allowed more sophisticated and accurate assessments.
Currently, studies show that pupillary reaction to light can help specialists make different types of diagnoses. Automated pupillometry is a system used for imaging the pupil that can help diagnose pathologies, physiological conditions, and cognitive or emotional state. It also allows to assess interest, effort in decision making, tiredness, fatigue, drug use and autonomic system functions.
According to research carried out by our group, published in Jornaul of Biomedical Informatics titled "Pupillary light reflex as a diagnostic aid from computational viewpoint: A systematic literature review" there are approximately 50 different physical conditions or pathologies that have been studied with the aid of pupillometry.
The practicality and assertiveness of pupillometry has aroused the interest of the research community and, thus, a considerable amount of research has been published in recent years to aid in diagnosis.

Methodology

In this project, eye movements are recorded using a device specially built and patented at the National Institute of Industrial Property. (INPI) number BR1020190076224.
The device ensures that ambient light does not interfere with the conduct of the procedure. It also allows the examiner a set of stimulus settings to produce the necessary reactions.


Pupil movements result from the balance between the activity of the iris sphincter muscle innervated by the parasympathetic nervous system responsible for pupillary contraction and the activity of the iris dilator muscle innervated by the sympathetic nervous system. The pupillary response to light graph reflects this movement recorded by the device.
The device control, initial validation and patient release, pre-processing and storage of the exam and finally the classification of the pupillary signal, a set of algorithms and Artificial Intelligence techniques was developed by the researchers participating in the Eyes Project.

Partners in Eyes Project