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UCSD: Device for analyzing the state of the pupil

Product
Developers: University of California, San Diego (UCSD)
Date of the premiere of the system: November 2023
Branches: Pharmaceuticals, Medicine, Healthcare

2023: Product Announcement

On October 24, 2023, American engineers from the University of California, San Diego announced the development of a specialized accessory for smartphones that allows you to diagnose various neurological conditions. The device, in particular, is capable of detecting traumatic brain injuries and Alzheimer's disease.

The device is a camera nozzle smartphone that analyzes the state of the pupil. The researchers note that changes in pupil size when a patient performs certain tasks are associated with a person's neurological condition. For example, the pupil usually expands during complex cognitive activities or in response to unexpected stimuli.

Scientists at UCSD have developed a smartphone accessory that allows you to diagnose various neurological conditions

The difficulty, however, is that tracking pupil sizes can be difficult in people with dark eye color. The fact is that in this case, ordinary color cameras can hardly distinguish between the pupil and the iris. Therefore, the diagnostic results are not accurate enough. To solve the problem, experts from the University of California at San Diego equipped their device with a special filter that selectively transmits light with a certain wavelength into the camera - the so-called far red light (the range of visible light, between red and infrared).

Melanin, a dark iris pigment, absorbs most wavelengths of visible light but reflects longer wavelengths, including far red light. As a result, the iris appears significantly lighter, which makes it possible to determine the boundaries of the pupil with high accuracy.

You can use the accessory with any smartphones: just fix the nozzle on the camera of the device and apply it to the eye. The smartphone conducts a pupil reaction test, generating a flash of bright light and recording video. After that, the machine learning model determines the size of the pupil and concludes about the neurological state of the user.[1]

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