Release date: 2017-09-14
Concussion is a type of brain damage. In sports competitions and daily activities, people may cause concussion in case of accidental injury. In the past, screening and diagnosis of brain damage required identification in a professional medical institution, which took a lot of time in the process. 
Image source: University of Washington
Researchers at the University of Washington are developing the first smartphone app that can detect concussions objectively, and this app can also screen for other traumatic brain damage. Researchers expect the app to help those in need for the first time, such as in the midst of a sports game, on the battlefield, or in the homes of older people who are prone to falls.
How does the smartphone app help detect concussions and other brain damage?
The scientific basis it uses is a principle called pupil-to-light reflection (PLR). The pupil's reflection of light has long been used to assess whether a patient has severe traumatic brain damage. Clinically, this is one of the few methods that can be used to quantify brain damage. Clinically low-cost PLR testing is measured using a pen-sized flashlight. The clinician uses a flashlight to perform near and far detection around the eye to observe changes in the subject's pupil. Since such tests are evaluated by the clinician through observation, there is a lack of better accuracy in data reading. The researchers found that the average error of the data in such measurements was 0.5 mm, which is a very large number compared to the diameter of the pupil itself.
 
The clinician used a pen-sized flashlight to perform a pupillary light reflex test on the patient.
Image source: University of Washington
This is undoubtedly an improvement in the existing medical conditions. Is there any way to make this test more quantifiable and more convenient?
So, the researchers thought of smart phones, can you solve this problem through the application of smart phones?
The app called PupilScreen was born. PupilScreen can use the camera of a smartphone to observe the pupil's response to light. The APP not only calls the camera, but also combines the most advanced deep learning tools available today – a type of artificial intelligence. Deep learning can quantify subtle changes in human pupils. The APP uses the flash of the smartphone to stimulate the patient's eyes and uses the camera to record a three-second video. 
The camera of the smartphone recorded a small change in the pupil. Image Source: medgadget
This video is processed using a deep learning algorithm that determines which pixel in each video frame belongs to the pupil and measures the change in pupil size in those frames. In a small pilot study, 48 cases from patients with traumatic brain injury and healthy people were covered, and clinicians diagnosed almost complete brain damage with the help of the application.
As described in the paper published by Ubicomp on September 13, 2017, PupilScreen can assess the patient's pupillary light reflection, which is almost comparable to the pupil measurement instrument. The pupil measuring instrument is an expensive and rarely used machine that can only be found in hospitals.
The US Centers for Disease Control and Prevention estimates that half of the 3.8 million concussions in the United States are still unresolved, and millions of young players and adults face the future. The risk of injury and permanent cognitive impairment.
PupilScreen can help them screen their brain damage immediately at the injured site so that these athletes or other people in need can get the right diagnosis in the first place, and then get timely and effective treatment. Many times, in the emergency room, doctors still rely on the observation of the naked eye to judge whether brain damage occurs. Mild concussion has only a small pupillary change that is difficult to accurately measure with the naked eye. Now, with PupilScreen, smartphones can be used to detect mild concussions, which opens up a whole new way of thinking about concussion screening.
Source: Health New Vision
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