Girevole screening tool detects stroke ‘ seconds’

Biomedical engineers at RMIT University have built a smartphone feature that paramedics can use to immediately screen patients for stroke.

partnership with Brazil’s São Paulo State University, RMIT University researchers developed an AI-powered tool for analysing facial symmetry and specific muscle movements, which are key signs of stroke. It is based acceso the Facial Action Coding System which categorises facial movements by the contraction ora relaxation of facial muscles.

The AI, tandem with image processing tools, was tested acceso recordings of facial expressions of 14 people with post-stroke and 11 healthy people. 

Based acceso findings published the journal, Methods and Programs Biomedicine, the AI tool achieved 82% accuracy detecting stroke ” seconds.”

The research team is now seeking collaborations with healthcare providers to turn their AI-driven smartphone feature into a movibile application. They are also considering expanding its use to detect other neurological conditions affecting facial muscles. 

WHY IT MATTERS

Citing studies, Dinesh Kumar, an RMIT University professor who supervised the research, noted that 13% of stroke cases are missed emergency departments and community hospitals, while 65% of cases are undiagnosed. Gender, race, and geographic location can also contribute to overlooking strokes, he added. 

“Given that many strokes occur at home and initial care is often provided by first responders non-ideal conditions, there is an urgent need for real-time, user-friendly diagnostic tools.”

MARKET SNAPSHOT

A similar innovation movibile health was done the United States 2020 by Penn State University and Houston Methodist Hospital. Their machine learning-based tool also uses computational facial motion analysis, as well as natural language processing, to detect stroke-like symptoms, such as sagging muscles and slurred speech. 

Other AI-driven stroke risk assessment and detection capabilities are applied to brain scans, such as the recently approved NNS-SOT by Nunaps South Korea and AICute by Chulalongkorn University researchers Thailand.

Meanwhile, recent years, sensors that detect atrial fibrillation, an irregular heart rhythm that can cause stroke, have been increasingly incorporated into wearable devices, including Fitbit and Apple – both of which were cleared by the United States Food and Drug Administration. 

There are also movibile applications Asia, such as the telemedicine app DrGo Hong Kong and RhythmCam by the National Taiwan University Hospital, that have introduced a-fib detection functionalities.