The Irregular Rhythm Notification Feature is a software-only mobile medical application that is intended to be used with the Apple Watch. The feature analyzes pulse rate data to identify episodes of irregular heart rhythms suggestive of atrial fibrillation (AFib) and provides a notification to the user. The feature 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 feature 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 is still. Along with the user's risk factors, the feature can be used to supplement the decision for AFib screening. The feature is not intended to replace traditional methods of diagnosis or treatment.

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

Device Description

The Irregular Rhythm Notification Feature comprises a pair of mobile medical apps, one on Apple Watch and the other on the iPhone. The Irregular Rhythm Notification Feature analyzes pulse rate data collected by the Apple Watch photoplethysmograph (PPG) sensor to identify episodes of irregular heart rhythms consistent with atrial fibrillation (referred to in this document as AF or AFib) and provides a notification to the user. It is a background screening tool and there is no way for a user to initiate analysis of pulse rate data. The Irregular Rhythm Notification Feature is part of the Health App, which allows users to store, manage, and share health and fitness data, and comes pre-installed on every iPhone. Users must opt-in and go through onboarding prior to use of the Irregular Rhythm Notification Feature.

The Irregular Rhythm Notification Feature is not intended to diagnose atrial fibrillation, and is not intended to be used to guide clinical treatment or care.

AI/ML Overview

Here's a summary of the acceptance criteria and the study proving the device meets them, based on the provided text:

Acceptance Criteria and Device Performance for Irregular Rhythm Notification Feature

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly define a "table of acceptance criteria" with specific numerical targets in the same way an academic paper might. However, by synthesizing the "Clinical Study" section and the "Risks to Health" with their "Mitigation Measures," we can infer the key performance metrics and their achieved results. The pre-specified performance goal was explicitly stated for the primary endpoint.

Acceptance Criterion (Inferred from study objectives & risks)	Reported Device Performance
Primary Endpoint: Positive Predictive Value (PPV) of spot irregular tachograms to detect AF (against ambulatory ECG)	66.6% (lower 97.5% confidence bound: 63.0%). This failed to meet the pre-specified (0)% performance goal. (Note: The "0%" pre-specified goal seems like a typo in the original document and likely should have been a specific non-zero percentage. Given the context, they were looking for a high PPV.)
Secondary Endpoint: Notification-level PPV for AF in enriched population (users who received at least one prior notification)	78.9% (95% CI: 66.1%, 88.6%). (This metric, while not the primary, was supportive of effectiveness despite the primary endpoint failure.)
Probability of being diagnosed with AF on subsequent 7-day patch cardiac monitoring for subjects who received one or more device notifications (Post-hoc analysis)	41.6% (95% CI: 35.1%, 48.3%).
User comprehension of "lack of notification does not affect medical decisions"	36/37 participants successfully responded indicating this.
User comprehension of "would not reduce care if experiencing acute symptoms" upon receiving a notification	35/35 participants successfully received a notification and indicated this.
Software Validation	Moderate Level of Concern (LOC) guidelines met.
Functional Performance (Bench Testing)	Acceptable performance demonstrated against commercial, FDA-cleared clinical ECG.
Skin Tone Performance	No clinically relevant difference from Fitzpatrick VI to Fitzpatrick I subjects. No algorithm changes needed.
Detection of adequate PPG signal quality (Non-clinical performance testing)	Demonstrated.

2. Sample Size for the Test Set and Data Provenance

Clinical Study Test Set:
- Full Analysis Set (FAS): 269 subjects
- Analyzable ECG monitor and tachogram data: 226 subjects (after exclusions)
- Irregular tachograms recorded: 2634 (out of 10432 total tachograms during monitoring)
- Subjects receiving at least one alert: 57 (25.2% of the 226 analyzable subjects)
Data Provenance: The data was collected from a large, prospective, single-arm study conducted to investigate PPG data from Apple Watch for AF-related irregular heart rhythm identification. The sub-study enrolled participants who had already received one prior Irregular Rhythm notification. The country of origin is not explicitly stated but implies a broad user base given Apple's global reach, although the study itself was managed by Apple Inc. in Cupertino, CA.
Bench Testing Test Set:
- External Aggressor Condition Testing:
  - Riding in a car (vibration): 44 subjects, 1434 measurements
  - Targeted Hand + finger motions: 20 subjects, 246 measurements
  - Low perfusion: 102 subjects, 2461 measurements
  - Hand Tremors: 143 subjects, 936 measurements
- Skin Tone Performance: 1124 subjects, 1.3 million measurements
Human Factors and Usability Study Test Set: 37 participants (16 "Active Interest", 21 "Passive Interest")

3. Number of Experts and Qualifications for Ground Truth - Clinical Study

Number of Experts: Unspecified exact number of independent cardiologists. It states "independent cardiologists" (plural).
Qualifications: "Independent cardiologists" (no further details on experience or specialization, but the title implies appropriate medical expertise).

4. Adjudication Method for the Test Set - Clinical Study

The document states: "For each one-minute irregular rhythm episode (tachogram) identified by the software, the corresponding patch ECG recording was extracted and classified by independent cardiologists as either 'Sinus rhythm', 'AF', 'Unreadable', or 'Other Irregular Rhythm.'" This implies a single expert classification or a pre-defined process without explicitly stating a consensus method like 2+1 or 3+1.

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

No, an MRMC comparative effectiveness study was not done or reported comparing human readers with and without AI assistance. The clinical study focused on the standalone performance of the device's notification feature against an ambulatory ECG.

6. Standalone (Algorithm Only) Performance

Yes, the primary clinical study was a standalone (algorithm only) performance evaluation. The device independently identified irregular rhythm episodes, which were then compared to the ground truth established by ambulatory ECG and cardiologist review. There was no human-in-the-loop component for the detection performance evaluation itself.

7. Type of Ground Truth Used

Clinical Study:
- For the primary and secondary endpoints related to AF detection, the ground truth was established by 7-day ambulatory patch ECG recordings, which were then "classified by independent cardiologists as either 'Sinus rhythm', 'AF', 'Unreadable', or 'Other Irregular Rhythm.'" This combines outcomes data (ECG) with expert consensus/interpretation.
Bench Testing:
- Functional performance: Compared to "commercial, FDA-cleared clinical ECG."
Human Factors Study:
- User comprehension: Observational data and subjective evaluations of user responses to questions.

8. Sample Size for the Training Set

The document does not explicitly state the sample size for the training set used to develop the Irregular Rhythm Notification Feature algorithm. It only describes the evaluation of the algorithm on the described test sets.

9. How the Ground Truth for the Training Set Was Established

The document does not explicitly describe how the ground truth for the training set was established. It focuses only on the validation study. It can be inferred that similar methods (ECG data interpreted by cardiologists) would likely have been used during development, but this is not detailed in the provided text.

Summary

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DE NOVO CLASSIFICATION REQUEST FOR IRREGULAR RHYTHM NOTIFICATION FEATURE

REGULATORY INFORMATION

FDA identifies this generic type of device as:

Photoplethysmograph analysis software for over-the-counter use. A photoplethysmograph analysis software device for over-the-counter use analyzes photoplethysmograph data and provides information for identifying irregular heart rhythms. This device is not intended to provide a diagnosis.

NEW REGULATION NUMBER: 21 CFR 870.2790

CLASSIFICATION: Class II

PRODUCT CODE: QDB

BACKGROUND

DEVICE NAME: Irregular Rhythm Notification Feature

SUBMISSION NUMBER: DEN180042

DATE OF DE NOVO: August 8, 2018

CONTACT: Apple Inc. One Apple Park Way Cupertino, CA 95014

INDICATIONS FOR USE

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

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LIMITATIONS

The Irregular Rhythm Notification Feature cannot detect heart attacks. If you ever experience chest pain, pressure, tightness, or what you think is a heart attack, call emergency services.

The Irregular Rhythm Notification Feature is not constantly looking for AFib and should not be relied on as a continuous monitor. This means the feature cannot detect all instances of AFib, and people with AFib may not get a notification.

Apple Watch may be unable to collect data when Apple Watch is in close vicinity to strong electromagnetic fields (e.g. electromagnetic anti-theft systems, metal detectors).

A number of factors can impact the ability of the feature to measure your pulse and detect an irregular rhythm suggestive of AFib. These include factors like motion, hand and finger movements, dark tattoos on the wrist, and the amount of blood flow to your skin (which can be reduced by cold temperatures).

DO NOT wear your Apple Watch during a medical procedure (e.g., magnetic resonance imaging, diathermy, lithotripsy, cautery and external defibrillation procedures).

DO NOT change your medication without talking to your doctor.

Not intended for use by individuals under age 22.

Not intended for use by individuals previously diagnosed with AFib. Notifications made by this feature are potential findings, not a complete diagnosis of cardiac conditions. All notifications should be reviewed by a medical professional for clinical decision-making.

Apple does not guarantee that you are not experiencing an arrhythmia or other health conditions even in the absence of an irregular rhythm notification. You should notify your physician if you experience any changes to your health.

PLEASE REFER TO THE LABELING FOR A MORE COMPLETE LIST OF WARNINGS, PRECAUTIONS AND CONTRAINDICATIONS.

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DEVICE DESCRIPTION

The Irregular Rhythm Notification Feature is not intended to diagnose atrial fibrillation, and is not intended to be used to guide clinical treatment or care.

Platform/PPG

The Irregular Rhythm Notification Feature leverages heart rate data collected from the commercially available PPG sensor on Series 1 and later Apple Watch platforms. The Apple Watch uses green LED lights paired with light-sensitive photodiodes to detect relative changes in the amount of blood flowing through a user's wrist at any given moment. When the heart beats it sends a pressure wave down the vasculature, causing a momentary increase in blood volume when it passes by the sensor. By monitoring these changes in blood flow, the Apple Watch can measure the heart rate. Further, under stationary conditions the sensor can detect individual pulses when they reach the periphery and thereby measure the beat-to-beat intervals.

A schematic of the sensors on the Apple Watch (Series 1-3) is provided below.

Image /page/2/Figure/6 description: The image shows a diagram of the back of an Apple Watch, highlighting its sensor technology. Two green circles labeled as "Green and infrared LEDs" are positioned on the left and right sides. Above these, an arrow points to two gray circles, identified as "Photodiode sensors," indicating their placement and function within the watch's health-monitoring system.

Currently, Apple Watch attempts to collect and analyze a one-minute beat-to-beat sequence (called a "tachogram") in the background (i.e., with no user action required) approximately every 4 hours, depending on user activity. A minimum of (b) (4) pulses is required for a measurement to be considered successful and stored in HealthKit; measurements are stored as beat-to-beat time intervals. Measurements that do not meet the specification are discarded and never surfaced to the user in anv form.

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Irregular Rhythm Notification Feature

The Irregular Rhythm Notification Feature refers to the tachogram classification algorithm, confirmation cycle algorithm, and the AF notification generation. Tachogram analysis is initiated when the Irregular Rhythm Notification Feature retrieves a new tachogram from Watch HealthKit. Tachograms are classified as either irregular or not AF. If a sufficient number of tachograms are retrieved and classified to meet the notification threshold (5 of 6 sequential tachograms classified as irregular within a 48-hour period), a notification that the heart rhythm has shown signs of AF will be displayed to the user. Individual tachogram classification results for sequences that do not meet the notification threshold are not accessible to the user. If an irregular heart rhythm suggestive of AF is identified, the Irregular Rhythm Notification Feature will transfer the AF notification to the iPhone App through HealthKit sync. In addition to indicating the finding of signs of AF, the notification will encourage the user to seek medical care if thev have not previously been diagnosed with AF.

iPhone App

Apple considers the iPhone App to be the Irregular Rhythm Notification Feature User Interface (UI) Framework as well as the information included in the Atrial Fibrillation Notification portion of the Health App. The Irregular Rhythm Notification Feature UI Framework contains the onboarding and educational materials that a user must review prior to enabling AF notifications. The iPhone App is designed to work in combination with the Irregular Rhythm Notification Feature Watch App and will display a history of all prior atrial fibrillation notifications. The user is also able to view a list of times when each of the irregular tachograms contributing to the notification was generated.

SUMMARY OF NONCLINICAL/BENCH STUDIES

SOFTWARE

Irregular Rhythm Notification Feature has a Moderate Level of Concern (LOC). Appropriate documentation was provided to support the validation of the software for a Moderate LOC in accordance with FDA's 2005 guidance titled, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices."

PERFORMANCE TESTING - BENCH

Irregular Rhythm Notification Feature was subjected to a series of bench tests to assess its functional performance. These tests were performed on a version of the device that was sufficiently representative of the final version of the engineering bench testing summarized in the table below was performed to demonstrate acceptable performance of the device for its intended use. Bench testing results were compared to commercial, FDA-cleared clinical ECG.

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Test	Description
Deep Breathing Testing	Evaluate performance during sinus rhythm variation due to respiratory sinus arrhythmia.
External AggressorCondition testing	Riding in a car(vibration)44 subjects, 1434measurements
	Targeted Hand +finger motions20 subjects, 246measurements
	Low perfusion102 subjects, 2461measurements
	Hand Tremors143 subjects, 936measurements
	Determine the effect offactors known to lead tosystematic false positivespot measurements for anyindividual or use case.
Skin Tone Performance	Validation of algorithm performance on PPG acquiredacross 1124 subjects, 1.3 million measurements. Algorithmperformance showed no clinically relevant difference fromthe very darkest Fitzpatrick VI subjects to very light-skinned Fitzpatrick I subjects. No algorithm changes orsignal processing modifications are necessary to accountfor differences in skin tone.
	Input Signal Source Qualification

SUMMARY OF CLINICAL INFORMATION

Clinical Study

The sponsor provided a clinical study protocol and results to support the safety and effectiveness of the device. This study used data collected from a subset of participants enrolled in a large, prospective, single-arm study conducted to investigate if the PPG data collected by the Apple Watch can be used to identify episodes of AF-related irregular heart rhythm in users without known atrial fibrillation. The sub-study enrolled only those participants from the the larger study who received one prior Irregular Rhythm notification.

Once enrolled, the study participants wore their Apple Watch with the Irregular Rhythm feature as per normal usage while being monitored with a 7-day ambulatory patch ECG recorder. For each one-minute irregular rhythm episode (tachogram) identified by the software, the corresponding patch ECG recording was extracted and classified by independent cardiologists as either "Sinus rhythm", "AF", "Unreadable", or "Other Irregular Rhythm." The primary objective of the study is to determine if the tachogram classification algorithm has acceptable positive predictive value as compared to ambulatory ECG patch monitoring in identifying irregular rhythms consistent with atrial fibrillation.

A total of 269 subjects were included in the Full Analysis Set (FAS). The mean age was 59.2 ± 13.3 years, and 80.2% (210/269) were male. Of the 269 subjects, 27 were removed from the FAS due to data exclusions and 16 subjects were removed due to lack of ambulatory ECG monitor data. Accordingly, 226 subjects provided analyzable ECG monitor data and tachogram data and were included in the efficacy analyses. Among these 226 subjects during the ambulatory ECG

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monitoring (on average of 6.3 days), 2634 (out of a total of 10432 tachograms) irregular tachograms were recorded, and 57 subjects (25.2%) received at least one alert. Using the ambulatory ECG monitor data as the reference, the positive value (PPV) of spot irregular tachograms to detect AF was 66.6% (lower 97.5% confidence bound: 63.0%). The results failed to meet the pre-specified (0) % performance goal.

Despite failing to meet the primary study endpoint, the results of secondary and additional analyses are supportive of the device's effectiveness to detect AF. Per the protocol-specified secondary analysis, the notification-level PPV for AF in this enriched population was 78.9% (95% C1: 66.1%, 88.6%). A post hoc analysis was also performed to determine the proportion of subjects who had documented atrial fibrillation during the entire 7-day patch cardiac monitoring. Of the 226 subjects, who already received one or more device notifications before enrolling in the sub-study, the probability of being diagnosed with AF on subsequent 7-day patch cardiac monitoring was 41.6% (95% CI: 35.1%, 48.3%).

Human Factors and Usability Study

The sponsor provided a Human Factors and Usability study which included a total of 37 participants from the two user groups for the Irregular Rhythm Notification Feature:

. Individuals who have concern regarding arrhythmias and have an active interest in monitoring potential arrhythmias ("Active Interest", n=16), and
. Individuals who do not have concern regarding arrhythmias and do not have an active interest in monitoring potential arrhythmias but who might use the app out of casual or passing interest ("Passive Interest", n=21).

Both groups included participants with and without past experiences with iPhones and Apple Watches.

All participants set up the app, which was meant to simulate the actual on-boarding process. The participants then experienced a decay period of approximately 1 hour, and then a testing session that lasted approximately 30 minutes. Sessions took place in a simulated home environment representative of an expected environment of use in real life. Both observational data and subjective evaluations were collected.

Overall, usability testing demonstrated that the Irregular Rhythm Notification Feature is safe and effective for the intended users, uses, and use environments. In particular:

. 36/37 participants successfully responded indicating that a lack of a notification from the App would not affect their medical decisions.
. 35/35 participants successfully received a notification and indicated they would not reduce care if experiencing acute symptoms.

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Pediatric Extrapolation

The device is indicated for use only in adults - that is, persons aged 22 and older. The Federal Food, Drug, and Cosmetic Act defines pediatric patients as persons aged 21 or younger. In this De Novo request, existing clinical data were not leveraged to support the use of the device in a pediatric patient population.

LABELING

The labeling for the device is sufficient and satisfies the requirements of 21 CFR 801.109. The labeling consists of Instructions for Use and an onboarding sequence. The Instructions for Use include the indications for use; a description of the device, precautions; a detailed summary of the clinical data collected in support of the device; a list of potential adverse events; and instructions for the safe use of the device.

Please see the Limitations section above for important contraindications, warnings and precautions presented in the device labeling.

RISKS TO HEALTH

The table below identifies the risks to health that may be associated with use of photoplethysmograph analysis software for over-the-counter use and the measures necessary to mitigate these risks.

Identified Risk	Mitigation Measures
Poor quality incoming PPG signal resulting in failure to detect irregular heart rhythms	Clinical performance testingHuman factors testingLabeling
Misinterpretation and/or over-reliance on device output, leading to:Failure to seek treatment despite acute symptoms (e.g., fluttering sensation in the chest, lightheadedness, and irregular pulse) Discontinuing or modifying treatment for chronic heart condition	Human factors testingLabeling
False negative resulting in failure to detect irregular heart rhythms and delay of further evaluation or treatment	Clinical performance testingSoftware verification, validation, and hazard analysisNon-clinical performance testingLabeling

Identified Risks to Health and Mitigation Measures

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False positive resulting in additionalunnecessary medical procedures	Clinical performance testing
	Software verification, validation, and hazard analysis
	Non-clinical performance testing
	Labeling

SPECIAL CONTROLS:

In combination with the general controls of the FD&C Act, the photoplethysmograph analysis software for over-the-counter use is subject to the following special controls:

1. Clinical performance testing must demonstrate the performance characteristics of the detection algorithm under anticipated conditions of use.
1. Software verification, validation, and hazard analysis must be performed. Documentation must include a characterization of the technical specifications of the software, including the detection algorithm and its inputs and outputs.
1. Non-clinical performance testing must demonstrate the ability of the device to detect adequate PPG signal quality.
1. Human factors and usability testing must demonstrate the following:
- The user can correctly use the device based solely on reading the device labeling; a. and
- b. The user can correctly interpret the device output and understand when to seek medical care.
1. Labeling must include:
- a. Hardware platform and operating system requirements;
- b. Situations in which the device may not operate at an expected performance level;
- A summary of the clinical performance testing conducted with the device: C.
- d. A description of what the device measures and outputs to the user; and
- Guidance on interpretation of any results. e.

BENEFIT/RISK DETERMINATION

The Irregular Rhythm Notification Feature is an effective device for identifying abnormal pulse rates that may suggest the presence of atrial fibrillation. When a user receives one or more alerts from the device, the probability of diagnosing AF via subsequent 7-day ambulatory cardiac ECG monitoring is 41.6%. The device is not intended to diagnose AF, but it provides an accessible tool to identify individuals who are likely to benefit from further AF screening with ECG-based methods. It can be used to prescreen persons outside of the traditional high-risk population (i.e., age < 65 years) to improve the subsequent diagnostic yield of AF screening.

The risks of the device are mostly associated with false positive and false negative results, which can lead to either delay of further treatment (false negative) or unnecessary medical procedures (false positive). Clinical testing, under the conditions of use, is required to: 1) ensure that the device

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is provided with sufficient incoming PPG signal quality, and 2) characterize the likelihood of false results. Labeling is also required to help the user interpret the results they receive. Here, the labeling specifically states that the feature is not intended to replace traditional methods of diagnosis and that diagnosis for AF should still be done by ECG confirmation.

Even when the device provides a true result, there is also a probable risk of users misinterpreting the device output and using it to disregard acute symptoms indicative of a heart attack; alternatively, users may interpret the device output as providing permission to avoid compliance with an existing prescribed treatment for a chronic heart condition. Users may also view the device as providing a definitive diagnosis of AF even though a positive result is intended only to notify the user of an irregular rhythm suggestive of AF and supplement the decision for AF screening. However, this risk of misinterpretation can be mitigated through labeling and requiring a human factors evaluation of whether users understand how the device output should be interpreted and when to seek further care from a physician.

Since AF is associated with serious potential complications, a device that can provide early detection or improve the efficiency of AF screening is clinically valuable. On a large scale, the benefits to health of improved AF detection outweighs the risks of false results and misinterpretation. There is a reasonable assurance of safety and effectiveness for the device when used as intended.

Patient Perspectives

This submission did not include specific information on patient perspectives for this device.

Benefit/Risk Conclusion

In conclusion, given the available information above, the data support that for the software analysis of PPG data for the identification of irregular heart rhythm that may indicate the presence of AF in a general population, the probable benefits outweigh the probable risks for the Irregular Rhythm Notification Feature. The device provides benefits and the risks can be mitigated by the use of general controls and the identified special controls.

CONCLUSION

The De Novo request for the Irregular Rhythm Notification Feature is granted and the device is classified under the following:

Product Code: QDB Device Type: Photoplethysmograph analysis software for over-the-counter use Class: II Regulation: 21 CFR 870.2790

Regulation Number and Section

§ 870.2790 Photoplethysmograph analysis software for over-the-counter use.

(a)
Identification. A photoplethysmograph analysis software device for over-the-counter use analyzes photoplethysmograph data and provides information for identifying irregular heart rhythms. This device is not intended to provide a diagnosis.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Clinical performance testing must demonstrate the performance characteristics of the detection algorithm under anticipated conditions of use.
(2) Software verification, validation, and hazard analysis must be performed. Documentation must include a characterization of the technical specifications of the software, including the detection algorithm and its inputs and outputs.
(3) Non-clinical performance testing must demonstrate the ability of the device to detect adequate photoplethysmograph signal quality.
(4) Human factors and usability testing must demonstrate the following:
(i) The user can correctly use the device based solely on reading the device labeling; and
(ii) The user can correctly interpret the device output and understand when to seek medical care.
(5) Labeling must include:
(i) Hardware platform and operating system requirements;
(ii) Situations in which the device may not operate at an expected performance level;
(iii) A summary of the clinical performance testing conducted with the device;
(iv) A description of what the device measures and outputs to the user; and
(v) Guidance on interpretation of any results.