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The Fitbit Irregular Rhythm Notifications is a software-only mobile medical application that is intended to be used with compatible consumer wrist-worn products to analyze pulse rate data to identify episodes of irregular heart rhythms suggestive of atrial fibrillation (AFib) and provide a notification to the user.

The Fitbit Irregular Rhythm Notifications is intended for over-the-counter (OTC) use. It is not intended to provide a notification on every episode of irregular rhythm suggestive of AFib and the absence of a notification is not intended to indicate no disease process is present; rather the Fitbit Irregular Rhythm Notifications is intended to opportunistically surface a notification of possible AFib when sufficient data are available for analysis.

These data are only captured when the user's still. Along with the user's risk factors, the Fitbit irreqular Rhythm Notifications can be used to supplement the decision for AFib screening. The Fitbit Irregular Rhythm Notfications is not intended to replace traditional methods of diagnosis or treatment.

The Fitbit Irregular Rhythm Notifications has not been tested for use in people under 22 years of age. It is also not intended for use in individuals previously diagnosed with AFib.

The Fitbit Irreqular Rhythm Notifications consists of an algorithm that classifies pulse rate data, and a mobile application run within the Fitbit app that serves as the user interface (UI) and device display.

The Fitbit Irregular Rhythm Notifications leverages pulse rate data collected from compatible commercially available, general purpose wrist-worn products (e.g., smartwatch or fithess tracker). Photoplethysmograph (PPG) sensors consist of light-emitting diodes (LED) and photodiodes that detect changes in blood flow of a user's vasculature at any given moment. When the heart beats, it sends a pressure wave through the vasculature causing a blood flow increase. By monitoring the fluctuations the consumer wrist-worn products can measure pulse rate data. When the user is still the sensor detects when individual pulses reach the periphery (i.e., wrist) and measures beat-to-beat intervals.

If the analyzed data are consistent with signs of atrial fibrillation, a notification indicating that a heart rhythm showing signs suggestive of AFib will be displayed to the user. The Fitbit Irregular Rhythm Notifications will only surface a notification of a heart rhythm showing signs of AFib once in a 24-hour period.

The Fitbit Irregular Rhythm Notifications mobile app functions within the Fitbit consumer application and is run on a compatible, user-provided general purpose mobile computing product (e.g., smartphone or tablet). The Fitbit Irregular Rhythm Notifications mobile app serves as the display/user interface for the Fitbit Irregular Rhythm Notifications.

Acceptance Criteria and Device Performance for Fitbit Irregular Rhythm Notifications

1. Table of Acceptance Criteria and Reported Device Performance

The provided document focuses on the substantial equivalence to a predicate device rather than explicitly stating acceptance criteria as a numerical target. However, it details the performance metrics demonstrated by the clinical study to support this equivalence. The key performance metric reported is the Positive Predictive Value (PPV) for AFib detection.

2. Sample Size and Data Provenance

• Test Set Sample Size: 225 subjects received a positive algorithm detection and wore an ECG patch for comparison.
• Data Provenance: The study recruited subjects from Fitbit's U.S. user population. The data is prospective, as users consented and were instructed to perform specific actions (schedule a telehealth visit, wear an ECG patch) following algorithm detection.

3. Number of Experts and Qualifications for Ground Truth

The document states that "Data gathered from the ECG patch was analyzed by medical professionals to determine whether signs of AFib were present." It does not specify the exact number of experts or their detailed qualifications (e.g., "radiologist with 10 years of experience").

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method like 2+1 or 3+1. It states that "data gathered from the ECG patch was analyzed by medical professionals to determine whether signs of AFib were present," implying a single assessment or a consensus process not detailed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was mentioned. The study focused on the standalone algorithm's performance against ECG ground truth, not on how human readers improve with or without AI assistance.

6. Standalone (Algorithm Only) Performance

Yes, a standalone performance study was conducted. The clinical study evaluated the Fitbit Irregular Rhythm Notifications algorithm's ability to identify irregular heart rhythms suggestive of AFib. The reported PPV of 98.2% is a measure of this standalone algorithmic performance.

7. Type of Ground Truth Used

The ground truth used for the test set was ECG patch data analyzed by medical professionals. This is a direct measure of cardiac electrical activity, considered a gold standard for AFib diagnosis.

8. Sample Size for the Training Set

The document does not specify the sample size for the training set. It mentions that the clinical study "recruited subjects from Fitbit's U.S. user population, inviting them to participate in a study. Upon consent, users had their PPG data analyzed for signs consistent with AFib by the algorithm." This describes part of the clinical validation, but not the training process or the data used for it.

9. How Ground Truth for the Training Set Was Established

The document does not provide details on how the ground truth for the training set was established. It only describes the ground truth establishment for the clinical validation test set (ECG patch data analyzed by medical professionals).

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