*A preliminary study presented at the 2024 American Heart Association Scientific Sessions reveals that an AI-powered tool can identify high blood pressure and diabetes by analyzing brief videos of facial and palm skin.
The system, still in early development in Japan, detects subtle changes in blood flow linked to these conditions. Researchers suggest it could reduce reliance on blood tests, cuffs, or costly wearables, Pharmacy Times reports.
“This method may someday allow people to monitor their own health at home and could lead to early detection and treatment of high blood pressure and diabetes in people who avoid medical exams and blood tests,” Ryoko Uchida, BSc Pharm, a project researcher in the department of advanced cardiology at the University of Tokyo, said in a news release.
Per the Pharmacy Times, the study tested a high-speed video camera capturing face and palm recordings at 150 frames per second, combined with AI to analyze blood flow features and detect high blood pressure and diabetes. The AI algorithm demonstrated 94% accuracy in identifying stage 1 hypertension (blood pressure ≥130/80 mm Hg) compared to continuous blood pressure monitoring. For detecting elevated blood pressure, a 30-second video was 86% accurate, while a 5-second video reached 81%. When compared to hemoglobin A1c tests, the video-AI system was 75% accurate in diagnosing diabetes.
“I was surprised about the applicability of the blood flow algorithm to detect diabetes,” Uchida said in the news release. “However, some of the major complications of diabetes are peripheral neuropathy—weakness, pain, and numbness, usually in the hands and feet—and other diseases related to blood vessel damage. It makes sense that changes in blood flow would be a hallmark of diabetes.”
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“It is really exciting to see more research that identifies ways to diagnose high blood pressure and diabetes non-invasively, 2 major risk factors for cardiovascular disease,” Eugene Yang, MD, MS, clinical professor of medicine in the cardiology division at the University of Washington School of Medicine in Seattle, said in a news release. “While the results are promising, it is important to recognize the validation of these technologies is lacking.”
The study authors noted that further development is needed before the method can be used beyond research, including adding an algorithm to account for arrhythmias.
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