(73 days)
Not Found
Yes
The "Mentions AI, DNN, or ML" section explicitly states that the device includes a rhythm classification algorithm that leverages machine learning techniques, specifically a convolutional neural network.
No This device is not a therapeutic device.
Explanation: The device is described as a "background screening tool" that provides notifications of irregular heart rhythms suggestive of AFib. It explicitly states, "The feature is not intended to replace traditional methods of diagnosis or treatment." This indicates it is for identification and notification, not for active treatment or therapy.
Yes
The device analyzes pulse rate data to identify episodes of irregular heart rhythms suggestive of atrial fibrillation and provides a notification to the user, indicating a potential medical condition. While it is not intended to replace traditional methods of diagnosis, it is designed to "opportunistically surface a notification of possible AFib," which is a form of screening, leading users to seek medical care. This function, despite its limitations and OTC nature, aligns with the purpose of a diagnostic device to identify or suggest the presence of a disease.
Yes
The device is explicitly described as a "software-only mobile medical application" in the Intended Use section. While it utilizes data from the Apple Watch's PPG sensor, the device itself is the software that analyzes this data and provides notifications. The description focuses on the software components (mobile apps, algorithms) and their function.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs analyze samples taken from the human body. The Irregular Rhythm Notification Feature analyzes pulse rate data collected by a sensor on the Apple Watch, which is a non-invasive measurement from the surface of the skin. It does not involve the analysis of biological samples like blood, urine, or tissue.
- The intended use is for screening and notification, not direct diagnosis based on sample analysis. The device identifies irregular heart rhythms suggestive of AFib and provides a notification. While this information can supplement a decision for AFib screening, it is not a diagnostic test performed on a biological sample.
Therefore, while it is a medical device and a mobile medical application, it does not fit the definition of an In Vitro Diagnostic.
No
The letter does not state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The "Control Plan Authorized (PCCP) and relevant text" section explicitly states "Not Found".
Intended Use / Indications for Use
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 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 in people under 22 years of age. It is also not intended for use in individuals previously diagnosed with AFib.
Product codes
QDB
Device Description
Irregular Rhythm Notification Feature 2.0 (IRNF 2.0) is comprised of a pair of mobile medical apps - One on Apple Watch and the other on the iPhone.
IRNF 2.0 is intended to analyze pulse rate data collected by the Apple Watch PPG sensor on Apple Watch Series 3. Series 4. Series 5. and SE to identify exisodes of irreqular heart rhythms consistent with AFib and provide 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. IRNF 2.0 iPhone App 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.
IRNF 2.0 Watch App refers to the rhythm classification algorithm, confirmation cvcle algorithm, and the AFib notification generation. If an irreqular heart rhythm consistent with Afib is identified and confirmed through the confirmation cycle, IRNF 2.0 Watch app will notify the user and transfer the AFib notification to the iPhone App through HealthKit sync. In addition to indicating the finding of signs of AFib, the notification will encourage the user to seek medical care.
IRNF 2.0 iPhone App contains the onboarding and educational materials that a user must review prior to use. IRNF 2.0 iPhone App is designed to work in combination with IRNF 2.0 Watch App and will display a history of all prior AFib notifications. The user is also able to view a list of times of the irreqular rhythms contributing to the notification.
Mentions image processing
Not Found
Mentions AI, DNN, or ML
IRNF 2.0 includes a new rhythm classification algorithm that leverages machine learning techniques to differentiate between AFib and non-AFib rhythms. The new rhythm classification algorithm uses a convolutional neural network based architecture and was trained extensively using data collected in a number of development studies.
Input Imaging Modality
Photoplethysmograph (PPG) data/pulse rate data
Anatomical Site
Not Found
Indicated Patient Age Range
The feature has not been tested for and is not intended for use in people under 22 years of age.
Intended User / Care Setting
over-the-counter (OTC) use
Description of the training set, sample size, data source, and annotation protocol
The studies used to train the convolutional network recruited demographically diverse populations with broad representation of age, sex, BMI, race, and skin tones. In total, the studies included over 2500 subjects and collected over 3 million pulse rate recordings on a variety of rhythms including: atrial fibrillation, normal sinus rhythm, sinus arrhythmia, and other ectopic beats (PVCs, PACs). For the purpose of developing the algorithm, the data was split into four sets with matching distributions of rhythms and demographics: Training, Validation, Testing, and Sequestration sets. The model was trained on the Training set, with the Validation set used for early stopping and threshold selection.
Description of the test set, sample size, data source, and annotation protocol
For the purpose of developing the algorithm, the data was split into four sets with matching distributions of rhythms and demographics: Training, Validation, Testing, and Sequestration sets. The model was then evaluated on the Testing set at reqular intervals during model development. When development was complete the model was locked, and then evaluated on the Sequestration set as a last test to ensure it had not been over-fit to the development data.
Summary of Performance Studies
Clinical Performance: The performance of the Irregular Rhythm Notification Feature (IRNF) was extensively tested in a clinical study of 573 participants ages 22 and older with a mix of diagnosed AFib and no known history of AFib. Enrolled subjects wore an Apple Watch and a reference electrocardiogram (ECG) patch concurrently for up to 13 days. For those subjects contributing data to the primary endpoint analysis, 32.4% (n=140/432) presented with AFib as identified on the reference ECG patch and were included in determining the device sensitivity. Of those, 124 received an IRNF irregular rhythm notification with concordant AFib on the ECG patch, and the sensitivity was 88.6%. Of the 292 subjects who did not present with AFib on the ECG patch and contributed data to the analysis of device specificity, 290 did not receive a notification. The AF detection specificity was 99.3%. The remaining subjects (n=141/573) either contributed data to only secondary endpoint analyses and/or did not complete the study. These results support the device's effectiveness in detecting AFib.
Key Metrics
Sensitivity: 88.6%
Specificity: 99.3%
Predicate Device(s)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 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.
0
Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
October 26, 2021
Apple Inc. Luke Olson Regulatory Affairs Associate 1 Apple Park Way Cupertino, California 95014
Re: K212516
Trade/Device Name: IRNF App Regulation Number: 21 CFR 870.2790 Regulation Name: Photoplethysmograph analysis software for over-the-counter use Regulatory Class: Class II Product Code: QDB
Dear Luke Olson:
The Food and Drug Administration (FDA) is sending this letter to notify you of an administrative change related to your previous substantial equivalence (SE) determination letter dated October 22, 2021. Specifically, FDA is updating this SE Letter due to a typo in the trade name as an administrative correction.
Please note that the 510(k) submission was not re-reviewed. For questions regarding this letter please contact Jennifer Shih Kozen, Office of Cardiovascular Devices, 301-796-5813, Jennifer.Shih(@fda.hhs.gov.
Sincerely,
Jennifer W. Shih -S
Jennifer Shih Kozen Assistant Director Division of Cardiac Electrophysiology, Diagnostics and Monitoring Devices Office of Cardiovascular Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
1
Image /page/1/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo in blue. Underneath the FDA logo is the word "ADMINISTRATION".
October 22, 2021
Apple Inc. Luke Olson Regulatory Affairs Associate 1 Apple Park Way Cupertino, California 95014
Re: K212516
Trade/Device Name: Irregular Ryhthm Notification Feature (IRNF) 2.0 App Regulation Number: 21 CFR 870.2790 Regulation Name: Photoplethysmograph analysis software for over-the-counter use Regulatory Class: Class II Product Code: QDB Dated: August 9, 2021 Received: August 10, 2021
Dear Luke Olson:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You mav, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's
2
requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-
542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE(@tda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Jennifer W. Shih -S
Jennifer Shih Kozen Assistant Director Division of Cardiac Electrophysiology, Diagnostics and Monitoring Devices Office of Cardiovascular Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
3
Indications for Use
510(k) Number (if known) K212516
Device Name Irregular Rhythm Notification Feature 2.0
Indications for Use (Describe)
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 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 in people under 22 years of age. It is also not intended for use in individuals previously diagnosed with AFib.
Type of Use (Select one or both, as applicable)
| Prescription Use (Part 21 CFR 801 Subpart D) | |
|---|---|
| Over-The-Counter Use (21 CFR 801 Subpart C) | X |
CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
4
510(k) Summary
This summary of 510(k) safety and effectiveness information is submitted in accordance with the requirements of 21 CFR §807.92:
5.1 Submitter
| Applicant | Apple Inc.
One Apple Park Way
Cupertino, CA 95014 |
|----------------------------|--------------------------------------------------------------------------------------------|
| Primary
Correspondent | Luke Olson
Regulatory Affairs
Phone: (408) 609-2001
Email: luke_olson@apple.com |
| Secondary
Correspondent | Dachan Kwon
Regulatory Affairs
Phone: (669) 268-5659
Email: dachan_kwon@apple.com |
| Date Prepared | August 09, 2021 |
5.2 Device Names and Classifications
Subject Device:
| Name of Device | Irregular Rhythm Notification Feature 2.0 |
|---|---|
| Classification Name | Photoplethysmograph Analysis Software For Over-The-Counter Use, |
| 21 CFR 870.2790 | |
| Regulatory Class | Class II |
| Product Code | QDB |
| 510(k) Review | |
| Panel | Cardiovascular |
Predicate Device:
| Predicate
| Manufacturer | Apple Inc. |
|---|---|
| Predicate Trade | |
| Name | Irregular Rhythm Notification Feature |
| Predicate 510(k) | DEN180042 |
5
5.3 Device Description
Irregular Rhythm Notification Feature 2.0 (IRNF 2.0) is comprised of a pair of mobile medical apps - One on Apple Watch and the other on the iPhone.
IRNF 2.0 is intended to analyze pulse rate data collected by the Apple Watch PPG sensor on Apple Watch Series 3. Series 4. Series 5. and SE to identify exisodes of irreqular heart rhythms consistent with AFib and provide 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. IRNF 2.0 iPhone App 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.
IRNF 2.0 Watch App refers to the rhythm classification algorithm, confirmation cvcle algorithm, and the AFib notification generation. If an irreqular heart rhythm consistent with Afib is identified and confirmed through the confirmation cycle, IRNF 2.0 Watch app will notify the user and transfer the AFib notification to the iPhone App through HealthKit sync. In addition to indicating the finding of signs of AFib, the notification will encourage the user to seek medical care.
IRNF 2.0 iPhone App contains the onboarding and educational materials that a user must review prior to use. IRNF 2.0 iPhone App is designed to work in combination with IRNF 2.0 Watch App and will display a history of all prior AFib notifications. The user is also able to view a list of times of the irreqular rhythms contributing to the notification.
5.4 Indications for Use
The Irreqular 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.
6
5.5 Comparison with the Predicate Device
| Item | Subject Device | Predicate Device |
|---|---|---|
| IRNF 2.0 App (K212516) | IRNF App (DEN180042) | |
| Manufacturer | Apple Inc. | Apple Inc. |
| Submission | ||
| Reference | K212516 | DEN180042 |
| Intended Use | 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. | 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. | ||
| Subject Device | Predicate Device | |
| ltem | IRNF 2.0 App (K212516) | IRNF App (DEN180042) |
| Indications for | ||
| Use | 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 | 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 | ||
| Principle of | ||
| Operation | The IRN 2.0 acquires platform sensor | |
| data from Apple Watch. After | ||
| acquisition, the IRN 2.0 algorithms | ||
| analyze pulse rate data to identify | ||
| episodes of irregular heart rhythms | ||
| suggestive of atrial fibrillation (AFib) | ||
| and provides notification to the user. | The IRN app acquires platform sensor | |
| data from Apple Watch. After | ||
| acquisition, the IRN app algorithms | ||
| analyze pulse rate data to identify | ||
| episodes of irregular heart rhythms | ||
| suggestive of atrial fibrillation (AFib) | ||
| and provides notification to the user. | ||
| Item | Subject Device | Predicate Device |
| IRNF 2.0 App (K212516) | IRNF App (DEN180042) | |
| Clinical | ||
| Performance | Apple conducted a clinical validation | |
| study to assess the performance of | ||
| the subject IRNF 2.0 app relative to | ||
| that of the predicate device on a | ||
| common sensor dataset. |
IRNF 2.0 person-level sensitivity
(88.6%) and specificity (99.3%) were
both demonstrated to be non-inferior
to those of the predicate device. | In a study of 226 participants aged 22
years or older wearing Apple Watch
and an electrocardiogram (ECG)
patch concurrently, 57 participants
received AFib notifications.
Of those, 78.9% (45/57) showed
concordant AFib on the ECG patch,
while 98.2 % (56/57) showed AFib
and other clinically relevant
arrhythmias. |
| Compatibility
with Intended
Platforms | iOS version 15.5 or later
watchOS version 8.5 or later
Apple Watch Series 3, 4, 5, SE
iPhone 6s and later | iOS 12.1.1 and later
watchOS 5.1.2 and later
Apple Watch Series 1 and later
iPhone 5s and later |
7
8
5.6 Performance Testing
IRNF 2.0 was verified and validated according to Apple's internal design control processes and in accordance with the special controls for Photoplethysmograph Analysis software for over-the-counter use (21 CFR 870.2790). The testing demonstrated that the device performed according to its specifications and that the technological and performance criteria are comparable to the predicate device.
IRNF 2.0 includes a new rhythm classification algorithm that leverages machine learning techniques to differentiate between AFib and non-AFib rhythms. The new rhythm classification algorithm uses a convolutional neural network based architecture and was trained extensively using data collected in a number of development studies. In total, the studies included over 2500 subjects and collected over 3 million pulse rate recordings on a variety of rhythms including: atrial fibrillation, normal sinus rhythm, sinus arrhythmia, and other ectopic beats (PVCs, PACs).
9
The studies used to train the convolutional network recruited demographically diverse populations with broad representation of age, sex, BMI, race, and skin tones. Table 2 below summarizes approximate development study demographic characteristics:
| Age Group (years) | |
|---|---|
| =55 to =65 | 35.1% |
| Sex | |
| Male | 49.6% |
| Female | 50.4% |
| BMI (kg/m2) | |
| =18.5 to =25.0 to =30.0 | 32.9% |
| Race | |
| White | 71.5% |
| Black or African American | 18.0% |
| Other | 10.5% |
Table 2. Development Study Subject Demographics
For the purpose of developing the algorithm, the data was split into four sets with matching distributions of rhythms and demographics: Traininq, Validation, Testing, and Sequestration sets. The model was trained on the Training set, with the Validation set used for early stopping and threshold selection. The model was then evaluated on the Testing set at reqular intervals during model development. When development was complete the model was locked, and then evaluated on the Sequestration set as a last test to ensure it had not been over-fit to the development data.
10
5.7 Clinical Performance
The performance of the Irreqular Rhythm Notification Feature (IRNF) was extensively tested in a clinical study of 573 participants ages 22 and older with a mix of diagnosed AFib and no known history of AFib. Study demographic characteristics are summarized in Table 3 below:
| N=573 | |
|---|---|
| Age Group (years) | |
| =55 to =65 | 310 (54.1%) |
| Sex | |
| Male | 286 (49.9%) |
| Female | 287 (50.1%) |
| Ethnicity | |
| Hispanic or Latino | 38 (6.6%) |
| Non-Hispanic or Latino | 535 (93.4%) |
| Race | |
| White | 502 (87.6%) |
| Black or African American | 57 (9.9%) |
| Other | 14 (2.4%) |
Table 3. IRNF 2.0 Clinical Study Subject Demographics
Enrolled subjects wore an Apple Watch and a reference electrocardiogram (ECG) patch concurrently for up to 13 days. For those subjects contributing data to the primary endpoint analysis, 32.4% (n=140/432) presented with AFib as identified on the reference ECG patch and were included in determining the device sensitivity. Of those, 124 received an IRNF irregular rhythm notification with concordant AFib on the ECG patch, and the sensitivity was 88.6%. Of the 292 subjects who did not present with AFib on the ECG patch and contributed data to the analysis of device specificity, 290 did not receive a notification. The AF detection specificity was 99.3%. The remaining subjects (n=141/573) either contributed data to only secondary endpoint analyses and/or did not complete the study. These results support the device's effectiveness in detecting AFib.
11
5.8 Human Factors Testing
Compared to the predicate device, there is no change to the indications for use, intended user populations, intended part of body applied to, use environment, operating principle, user interactions, use related hazards, use scenarios and critical tasks for IRNF 2.0. As such, Apple leveraged the Usability Engineering Report generated during development of the predicate device.
5.9 Conclusion
IRNF 2.0 is substantially equivalent to IRNF as they are identical with respect to intended use and there are no differences in technological or performance characteristics that raise new questions of safety and effectiveness.