FibriCheck

FibriCheck is a software-based medical device that enables patients to self-monitor for atrial fibrillation by using a mobile device's camera to capture photoplethysmography (PPG) signals, which reflect heart rhythm. Clinical evaluation demonstrates that this PPG-based analysis of blood volume changes provides diagnostic accuracy for atrial fibrillation detection (sensitivity 95.60%, specificity 96.55%) comparable to single-lead ECG-based monitoring methods.

FibriCheck is medical device software designed for individuals diagnosed with, or at risk of developing, atrial fibrillation to perform self-tests and monitor their heart rhythms intermittently. The technology operates by using the optical sensor of a mobile device, such as a smartphone camera, to collect photoplethysmogram (PPG) data, which reflects changes in blood volume. This PPG data is then analyzed by the FibriCheck software to identify heart rhythm conditions, with a specific emphasis on detecting atrial fibrillation. Users have the option to share their recordings with physicians or monitoring services, and a companion web application is available for healthcare professionals to manage patient information and review the collected FibriCheck data. The clinical efficacy of FibriCheck was assessed in a study involving 223 participants, of whom 100 had atrial fibrillation. In this study, FibriCheck's performance was benchmarked against a 12-lead ECG, considered the gold standard. The results indicated that FibriCheck achieved a sensitivity of 95.60%, specificity of 96.55%, a positive predictive value of 95.60%, a negative predictive value of 96.55%, and an overall accuracy of 96.14%. These performance metrics were found to be comparable to those of the reference device, Kardia (AliveCor), which utilizes a single-lead ECG technique and reported metrics in the same study including a sensitivity of 94.09% and specificity of 97.47%. FibriCheck's software complies with relevant medical device software standards, including those for software lifecycle processes and usability engineering, and is classified as having a 'moderate' level of concern and Safety Class B.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. How does the FibriCheck algorithm differentiate atrial fibrillation from other common arrhythmias or signal noise using only photoplethysmography (PPG) data?; What are the specific patient characteristics (e.g., skin tone, peripheral circulation status, comorbidities) that might impact the accuracy and reliability of FibriCheck's PPG measurements?; How does the 60-second fixed recording duration of FibriCheck affect its sensitivity in detecting paroxysmal atrial fibrillation episodes, particularly those that are brief or infrequent, compared to devices with variable or longer recording capabilities?; What usability factors were identified during the IEC 62366-1 testing, and how might these influence real-world adherence and correct usage by the target patient population for self-testing?; Beyond diagnostic accuracy, what data exists on FibriCheck's impact on clinical outcomes, patient management, or healthcare utilization when integrated into routine atrial fibrillation monitoring?