A new smartphone app may help identify stroke symptoms as they are happening.
Preliminary research suggests the app, called FAST.AI, could be as accurate at diagnosing a stroke as a neurologist.
Early recognition of stroke symptoms may result in more timely treatment, which may minimize the long-term effects and improve chances of a full recovery.
Researchers explained that FAST.AI is a fully automated smartphone application for the detection of severe stroke using machine learning algorithms to recognize facial asymmetry, drooping of the muscles in the face, arm weakness and speech changes – all common stroke symptoms.
It uses a facial video of the patient to examine 68 facial landmark points; sensors that measure arm movement and orientation; and voice recordings to detect speech changes. Information from each test was sent to a database server for analysis.
The study is ongoing, and the mobile app is still in development and not yet available to the public.
However, researchers validated FAST.AI’s performance by testing nearly 270 patients with a diagnosis of acute stroke within 72 hours of hospital admission at four major metropolitan stroke centers in Bulgaria.
Neurologists who examined the patients tested the app and then compared the FAST.AI results with their clinical impressions.
The analysis found that the app accurately detected stroke-associated facial asymmetry in nearly 100 per cent of patients.
The app accurately detected arm weakness in more than two-thirds of the cases.
And while the slurred speech module remains to be fully validated and tested, the research team said that preliminary analysis confirmed that it may be able to reliably detect slurred speech.
Clot-busting medication should be administered within three hours after stroke symptoms begin. The faster the treatment is administered, the more likely for a better recovery.
An average of 1.9 million brain cells die every minute that a stroke goes untreated, according to the American Stroke Association.
Previous research has found that stroke patients who are treated within 90 minutes of their ﬁrst symptoms were almost three times more likely to recover with little or no disability compared to those who received treatment more than 90 minutes after symptoms begin.
Study author Professor Radoslav Raychev, of the University of California, Los Angeles, said: “Many stroke patients don’t make it to the hospital in time for clot-busting treatment, which is one reason why it is vital to recognize stroke symptoms and call 9-1-1 right away.
“These early results confirm the app reliably identified acute stroke symptoms as accurately as a neurologist, and they will help to improve the app’s accuracy in detecting signs and symptoms of a stroke.”
The findings are due to be presented at the American Stroke Association’s International Stroke Conference in Dallas next week.
American Stroke Association Stroke Council member Professor Daniel Lackland welcomed the research as a promising tool to address a major health challenge – how to prompt people with stroke symptoms to seek care in a short window of opportunity.
Prof Lackland, of the Medical University of South Carolina, said: “The app may help individuals assess the signs of a stroke without the need to recall the warning signs.”
Produced in association with SWNS Talker.
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