FLASH-AF: The Validation of the FibriCheck Application for the Detection of Atrial Fibrillation
FLASH-AF: The Validation of the FibriCheck Application for the Detection of Atrial Fibrillation
Optical sensing technologies have the potential to enable long-term heart rhythm monitoring. The medically certified and clinically validated FibriCheck technology has proven its value for spot-check measurements to detect AF. However, further validation and verification of this technology is necessary to evaluate the performance of the FibriCheck technology on different tools (smartphones and smartwatches). During this study the performance of various optical sensors, ranging from the camera in smartphones to the photodetector in smartwatches, will be explored and device and form-factor variability will be investigated. The objective is to define the accuracy of optical sensing systems in the detection of atrial fibrillation versus a reference traditional 12-lead ECG signal.
During this study the performance of various optical sensors, ranging from the camera in smartphones to the photodetector in smartwatches, will be explored and device and form-factor variability will be investigated. The objective is to define the accuracy of optical sensing systems in the detection of atrial fibrillation versus a reference traditional 12-lead ECG signal. Therefore, 2 groups will be created where different technologies will be investigated i.e. Group 1 will use various mobile devices and Group 2 will use various wearable devices. The recruitment of patients will be carried out in the framework of the usual care practice, where patients can be recruited at different moments throughout their current care-cycle.
Group 1: Smartphone based sensor: Here, the user needs to place the finger on the smartphone camera for 60 seconds to obtain high quality PPG waveforms. These waveforms are analysed using automated algorithms and stored under a unique anonymized study ID.
Group 2: Smartwatch based sensor: Here, a wearable device is used that is placed on the wrist and will record a PPG signal, similar as the smartphone camera, but with a specific PPG sensor. The data is extracted and processed by the FibriCheck software and the algorithms generate a diagnostic output which is stored under a unique anonymized study ID.
The hardware involved originates from different providers. Since FibriCheck is certified as stand-alone software, it is expected that it functions independently from different hardware sources. This hypothesis will be addressed in this study.
Smartphone devices that will be used in this research: Samsung, Huawei, Xiaomi, Apple, LGE, Lenovo and ZTE devices. Wearable devices that will be used in this research: Apple and Fitbit smartwatch devices.
Inclusion Criteria:
Exclusion Criteria: