Researchers develop a contactless, rapid screening method using facial video analysis to detect undiagnosed hypertension and diabetes, signalling a potential breakthrough in preventative cardiovascular care.
Artificial intelligence analysis of brief facial video clips may offer a fast, contactless way to spot people with undiagnosed hypertension and diabetes, according to research due to be presented at ESC Congress 2026. The work comes as millions of adults worldwide still live with these conditions without knowing it, even though both are major, preventable drivers of cardiovascular disease.
Researchers at the University of Tokyo and Institute of Science Tokyo tested whether everyday facial footage could be used as a screening tool. In a prospective study of 215 people, participants were filmed for a short period with a spectroscopic camera while the software examined blood-flow patterns, skin colour signals and pulse-wave dynamics, alongside standard clinical checks for blood pressure and diabetes.
The team reported that the algorithm identified hypertension with 95% accuracy from a 30-second recording and with 90.3% accuracy from a five-second clip. For diabetes, based on facial blood-flow patterns, the system reached 88.2% accuracy over 30 seconds and 81.2% over five seconds, according to the study summary released by ESC and EurekAlert. The programme could also estimate systolic blood pressure from facial video alone, although the researchers said wider validation is needed because one measure of error remained above the preferred standard.
Ryoko Uchida, the presenter from the University of Tokyo, said the aim was to build a contactless screening method that could work in ordinary settings and help find people who might otherwise remain undiagnosed. Nico Bruining, who chairs part of the ESC digital and AI programme, said the approach could extend screening beyond hospitals and help treatment start earlier, potentially reducing the risk of heart attacks, strokes and other cardiovascular complications.
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