Wristband Algorithm Detects Shockable Cardiac Arrests With 92% Accuracy in Clinical Validation

Overview

• The DETECT‑1b study, published Tuesday in Circulation: Arrhythmia and Electrophysiology, found a wrist algorithm detected induced shockable cardiac arrests with 92% accuracy in a clinical setting.
• Researchers at Radboud University Medical Center evaluated the device during ventricular tachycardia ablation or subcutaneous ICD implantation in 49 adults in the Netherlands, with a median age of 66 and 84% men.
• Across 59 events, the system identified 100% of ventricular fibrillation and 90% of pulseless ventricular tachycardia, with nine false alarms during about 125 hours of monitoring.
• The wristband uses photoplethysmography, a light sensor that reads blood‑flow pulses at the skin, and it triggers an alarm when pulse peaks vanish.
• Authors describe this as the first external patient‑data validation for a wrist approach and say next steps include larger everyday‑life trials, testing detection of non‑shockable rhythms, and building direct links to emergency dispatch and volunteer responder networks.