A smart wearable wristband may soon play a crucial role in detecting cardiac arrest and automatically alerting emergency responders. New research suggests that such technology could significantly improve survival rates, particularly for cardiac arrests occurring outside hospital settings, where events often go unwitnessed.
The device effectively acts as a “digital witness.” By continuously monitoring vital signs, it can recognize when the heart stops pumping blood and trigger an alert to emergency services or nearby trained responders. Given that survival chances decrease rapidly with every minute without intervention, earlier detection could be life-saving.
Strong performance
The findings are based on the DETECT-1b study, conducted among 49 adult patients in the Netherlands with known arrhythmias. During a routine medical procedure, life-threatening heart rhythms, ventricular fibrillation (VF) and pulseless ventricular tachycardia (pVT), were temporarily induced under controlled conditions.
The wearable device successfully detected cardiac arrest in 92% of cases. Notably, ventricular fibrillation was identified in 100% of instances, while pVT was detected in 90% of cases. In total, 59 “shockable” cardiac arrest events were recorded. These are rhythms that can be treated with defibrillation using an AED.
The system produced nine false-positive alerts over 125 hours of monitoring, a relatively low rate that researchers consider acceptable in light of the high detection accuracy. The research was published in Circulation: Arrhythmia and Electrophysiology.
Light-based sensing monitoring
The wristband relies on photoplethysmography (PPG), a light-based technology that measures changes in blood flow through the skin. While similar sensors are already widely used in consumer smartwatches, this device integrates a dedicated algorithm designed specifically to detect cardiac arrest.
According to lead author Roos Edgar of Radboud University Medical Center, the key innovation lies in its ability to provide continuous, unobtrusive monitoring in everyday life. “This is the first study to externally validate such an algorithm using real patient data,” she noted, highlighting an important step toward reliable real-world deployment.
Integration with emergency response systems
Senior investigator Judith Bonnes envisions integrating the wristband with emergency dispatch centres and volunteer responder networks. In the Netherlands, such systems already mobilise trained citizens to assist in cardiac emergencies. Automatic detection and alerting could further shorten response times, especially in unwitnessed cases.
By directly linking wearable technology to emergency infrastructure, the system could ensure that both ambulance services and nearby responders are notified immediately when a cardiac arrest is detected.
Further validation needed
Despite the encouraging findings, experts caution that additional research is required. Cameron Dezfulian of the American Heart Association, who was not involved in the study, pointed out that the clinical setting may not fully reflect real-world conditions.
He also noted that pulseless electrical activity, one of the most common cardiac arrest rhythms, was underrepresented in the dataset. Broader validation across different patient populations and real-life environments will therefore be essential.
The research forms part of the wider DETECT project, a collaboration between Dutch hospitals and industry partners aimed at developing a smart wristband capable of both detecting cardiac arrest and automatically activating emergency response systems.
If successfully implemented in daily practice, this technology could become a vital link in the chain of survival, thus helping to save lives when every second counts.
Wearable heart monitoring
Earlier this year, we reported on research by the University Health Network and the University of Toronto that showed that smartwatches could enable earlier detection of health deterioration in patients with heart failure. The study followed 217 patients over three months using consumer wearables that continuously tracked metrics such as heart rate, activity, and oxygen levels.
An AI model analyzed the data to estimate daily cardiorespiratory fitness, showing strong agreement with traditional hospital-based tests. A decline of 10% or more in this measure was linked to a more than threefold increase in the risk of unplanned hospital admission or emergency care. By capturing real-world patient data, smartwatches could function as early warning systems, offering a more dynamic view of health than periodic clinical assessments.
