Development of a wristband for automated cardiac arrest DETECTion and alerting of the emergency medical services
Development of a wristband for automated cardiac arrest DETECTion and alerting of the emergency medical services

Development of a wristband for automated cardiac arrest DETECTion and alerting of the emergency medical services

Smart wristband detects cardiac arrest and alerts emergency services within seconds to save lives

Periode
-
Looptijd
36 months
Deel van call / Programma
/
Projectpartners
Erasmus MC
Hartstichting
Detect
Reinier De Graaf
Corsano

Each year, thousands of individuals experience an out-of-hospital cardiac arrest. Rapid emergency response is critical, yet about half of these arrests go unnoticed due to the absence of bystanders. The DETECT project, a collaboration between (academic) hospitals and an industry partner, aims to develop a wrist-worn device that automatically detects cardiac arrest and alerts emergency medical services. This public-private partnership brings together medical, technological, and implementation expertise to create a wristband that can save lives in everyday settings. The Cardiowatch (Corsano Health) will be further developed to fulfill this goal. 

Sudden cardiac arrest is a major health concern, affecting approximately 15,000 people annually in the Netherlands alone. Survival rates remain low - on average, only 23% survive an out-of-hospital cardiac arrest, and even fewer if the event is unwitnessed. Time is critical: every minute without resuscitation reduces the chance of survival by 7 to 10%. Because many arrests occur at home or when individuals are alone, innovations that can bridge this time gap are urgently needed.  

The Cardiowatch wristband uses photoplethysmography (PPG) - a light-based method that measures blood flow in the wrist - to recognize cardiac arrest. To develop the cardiac arrest detection algorithm, PPG data were collected from patients undergoing short-lasting, controlled cardiac arrests during routine hospital procedures, such as transcatheter aortic valve implantation (TAVI) (DETECT-1a study). The algorithm was then validated with data from both induced (DETECT-1b) and spontaneous (DETECT-1c) arrests, including shockable and non-shockable heart rhythms. To reduce false alarms, motion data from an integrated accelerometer will be added to the model (DETECT-2). The wristband is currently being tested in the home environment by healthy volunteers and individuals at increased risk of cardiac arrest (DETECT-3). 

The deliverable is a wrist-worn cardiac arrest detection and emergency alerting system. If subsequent studies prove successful in real-world settings, this technology could significantly reduce time to treatment and increase out-of-hospital cardiac arrest survival rates. 

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