A new medical research study has revealed that wearable health devices combined with Artificial Intelligence (AI) may help predict dangerous blood pressure emergencies up to three days before they occur. The research, announced by the American Heart Association on November 2, 2026, suggests that continuously monitoring blood pressure patterns and other health signals could help doctors identify patients at risk of developing a serious hypertensive crisis. The findings offer promising possibilities for improving early detection and preventing life-threatening complications.
The study involved 4,190 adults between the ages of 40 and 85 who were receiving medical care at a hospital in Sindh, Pakistan. Participants were monitored between January 2025 and January 2026 using portable blood pressure monitors and wrist-worn fitness tracking devices. Researchers used AI technology to analyse 47 different health indicators, including blood pressure fluctuations, sleeping patterns, heart rate and heart rate variability.
During the 12-month study, 312 participants experienced a total of 418 hypertensive crises. Researchers discovered that the AI system could identify individuals at increased risk up to 72 hours before a potentially dangerous episode. One important warning sign was the failure of blood pressure to decrease normally during sleep. A sudden increase of more than 35 mmHg in blood pressure after waking was also associated with a significantly higher risk.
The findings further indicated that patients whose doctors received AI-generated alerts and adjusted their medication within 24 hours experienced approximately 61% fewer hypertensive crises and 45% fewer emergency department visits compared with those who did not receive timely intervention. However, researchers emphasised that the findings are preliminary and require further investigation in larger and more diverse populations. The technology is intended to support medical professionals rather than replace conventional blood pressure monitoring and clinical decisions
