Scientific studies

The DETECT project comprises various scientific studies aimed at developing a smart wristband for the automated detection of cardiac arrest and alerting of the emergency services. These studies are being conducted across multiple hospitals in the Netherlands.

Step 1

Development of automated cardiac arrest detection

The first step towards the development of a technological solution for automated cardiac arrest detection and alerting of the emergency medical services have been taken. The DETECT-1a study was an observational study involving approximately 300 patients who underwent a cardiac procedure during which a short-lasting cardiac arrest was induced. This occurs, for example, during procedures such as the placement of a new heart valve or testing of an implantable cardioverter defibrillator (ICD). We asked these patients to wear the wristband during the procedure. The wristband contains photoplethysmography sensors. Photoplethysmography is a simple technique that uses light reflection to determine blood flow. Using the collected photoplethysmography data, we taught the wristband to distinguish cardiac arrest from normal blood flow. Several hospitals are participating in this research, including Radboudumc, Erasmus MC, Maastricht UMC, and Amsterdam UMC.

Step 2

Development of fall detection

In the second phase, we are exploring whether we can enhance the reliability of the automated cardiac arrest detection algorithm with input from other sensors. Sensors are small devices that can measure bodily signals. Cardiac arrest is accompanied by fainting and often a sudden fall. An accelerometer records acceleration and provides information about human movements. Therefore, the accelerometer sensor could provide valuable information to rule out or confirm a cardiac arrest. After all, if someone continues to walk, it is unlikely to be a cardiac arrest. On the other hand, if someone suddenly becomes unwell, it may align well with a cardiac arrest. 
We asked healthy volunteers to mimic daily movements (such as walking, sitting, clapping) and simulate falls in a gymnasium while wearing the smart wristband with photoplethysmography and accelerometer sensors. Using this data, we will investigate whether we can detect and distinguish a sudden physical collapse from normal movements. 

Step 3

Investigating false cardiac arrest alarms

A feasible application of the smart wristband in practice requires very few false cardiac arrest alarms, as the emergency medical services should not be unnecessarily activated. Therefore, in the next phase, we will investigate how often a false alarm (false positive) occurs. We will also explore ways to prevent these false alarms, such as adjusting the algorithm, incorporating additional sensor data, or allowing users to cancel the alarm manually. For this study, we aim to recruit 300 healthy volunteers and patients to wear the wristband for a period of two months. 

This study will be initiated in the first half of 2024. Therefore, we are actively seeking volunteers! 
Are you interested to participate? For more information, please visit this webpage.

Step 4

Final validation of the prototype

During phase 4, we will investigate the performance of the final version (prototype) of the smart wristband in real-world scenarios. This involves equipping patients at high risk of life-threatening cardiac arrhythmias with the wristband. We specifically recruit patients with an Implantable Cardioverter Defibrillator (ICD). In the event of life-threatening cardiac arrhythmias, the ICD will provide treatment. Meanwhile, we will assess whether the wristband accurately detected the short-lasting cardiac arrest and if the alarm system functioned as intended."

Contact the researchers



Department of cardiology
Geert Grooteplein Zuid 10
6525 GA Nijmegen
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