Researchers have developed a new smartphone application that could come in handy for paramedics as it detects within seconds if a patient has suffered a stroke. As per the developers, the tool has an accuracy of 82 per cent. The report noted that it uses artificial intelligenece (AI) to analyse facial symmetry and muscles movements to detect stroke...READ THE FULL STORY HERE▶
Stroke detection: Scientists develop new facial recognition tool to identify early symptoms
The researchers can detect whether there are any change in the asymmetry to smile and that is a key detection.
New Delhi: The burden of stroke is increasing across the globe, including India. In India stroke is the fourth leading cause of death and the fifth leading cause of disability. According to earlier research, the incidence of stroke in India ranges between between 105 and 152/100,000 people each year. The stroke symptoms can be detected by signs like numbness, weakness or paralysis in the face, arm or leg, according to the Mayo Clinic.
Recently scientists have found an advanced way of detecting the early symptoms of stroke using a smartphone. Researchers have developed a new smartphone application that could come in handy for paramedics as it detects within seconds if a patient has suffered a stroke.
The developers of the tool that has an accuracy of 82 per cent. The report noted that it uses artificial intelligenece (AI) to analyse facial symmetry and muscles movements to detect stroke.
Signs that the tool detects
The scientists explained how and what kind of signs of stroke that the tool can detect. Some of them include, confusion, loss of control over muscle movement, impaired speech amd diminished facial expressions. The team of researchers also shared the trial results of the application in a study that was published in the journal of Computer Methods and Programs in Biomedicine.
The lead author of the study, Guilherme Camargo de Oliveira from the Royal Melbourne Institute of Technology (RMIT), Australia said while checking how the tool works, one of the main parameter that affects people with stroke is that their facial muscles that typically become unilateral, hence one side of the face behaves in a different ways from the other side of the face.
The tool holds 82 per cent accuracy
The researchers can detect whether there are any change in the asymmetry to smile and that is a key detection. The smartphone tool has an accuracy rating of 82 per cent for detecting stroke, a success rate that compares to the paramedics.
For the study, the team used video recording of facial expression of 14 people had suffered a stroke and 11 healthy individuals. Early detection of stroke is vital for timely intervention that my reduce the long-term risk of complications.
