United States: By analyzing the patient’s face, a novel smartphone application may enable paramedics to quickly diagnose a stroke in patients, which could be very dangerous to health and can occur anytime during the day.
According to experts, the AI-driven instrument examines certain muscle movements and facial symmetry to identify minute indications of stroke.
Innovative Stroke Detection
“A major characteristic that impacts individuals who have had a stroke is that their facial muscles usually become unilateral, meaning that one side of the face functions differently from the other,” lead researcher Guilherme Camargo de Oliveira, a PhD candidate at RMIT University in Melbourne, Australia, stated.
Innovative Stroke Detection De Oliveira stated in a university news release, “We have the AI tools and the image-processing tools that can detect whether there is any change in the asymmetry of the smile — that is the key to detection in our case.”
and facial symmetry to identify minute indications of stroke.
How It Works
According to a study published in the June edition of the journal Computer Methods and Programs in Biomedicine, when presented with video recordings of 14 stroke patients and 11 healthy individuals, the tool had an 82% accuracy rate in identifying stroke.
Expert Insights
“Our face-screening tool compares favorably to paramedics in terms of success rate for detecting stroke,” stated Dinesh Kumar, a professor at RMIT’s School of Engineering and senior researcher.
The researchers emphasized that the smartphone application would not take the place of the clinical diagnostic tests for stroke performed in hospitals.
But by connecting a patient’s symptoms to a potential stroke, it could be feasible to identify those who require medical attention.
A wasted blood vessel that leaks blood into the brain or a clogged artery that stops blood flow can cause strokes. Confusion, a partial or whole loss of motor function, difficulty speaking, and a reduction in facial emotions are all signs of a stroke.
Importance of Early Detection
Research shows that in emergency rooms and community hospitals, around 13% of strokes go undetected, and 65% of patients who don’t have a neurological test on file have an undetected stroke, according to Kumar.
“The symptoms are often extremely subtle,” Kumar continued. Furthermore, it is more likely that the symptoms will be overlooked if first responders are interacting with individuals who are not of their race or gender, particularly women and persons of color.