(162 days)
Yes
The document explicitly states that the device "includes a deep learning algorithm". Deep learning is a subset of machine learning.
No
The device explicitly states that it is "not intended to diagnose, treat, or aid in the management of sleep apnea," and its function is to provide a notification, not a therapeutic intervention.
No
The "Intended Use / Indications for Use" explicitly states that the device "is not intended to diagnose, treat, or aid in the management of sleep apnea." While it identifies patterns suggestive of sleep apnea and provides a notification, it disclaims diagnostic intent.
Yes
The device is explicitly described as a "software-only mobile medical application" in both the Intended Use and Device Description sections. While it utilizes data from the Apple Watch, the device itself is the software that processes this data and provides notifications.
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 description clearly states that the Sleep Apnea Notification Feature (SANF) analyzes Apple Watch sensor data, specifically accelerometer data. This data is collected externally from the body and does not involve the analysis of biological samples like blood, urine, or tissue.
- The intended use is not for in vitro examination. The intended use is to identify patterns of breathing disturbances suggestive of sleep apnea and provide a notification to the user. This is based on analyzing physiological data collected by a wearable device, not on examining samples in a laboratory setting.
Therefore, while it is a medical device and utilizes sensor data and algorithms, it does not fit the definition of an In Vitro Diagnostic device.
Yes
FDA's substantial equivalence determination included the review and clearance of the Predetermined Change Control Plan (PCCP) for this specific device.
Intended Use / Indications for Use
The Sleep Apnea Notification Feature (SANF) is a software-only mobile medical application that analyzes Apple Watch sensor data to identify patterns of breathing disturbances suggestive of moderate-to-severe sleep apnea and provides a notification to the user. This feature is intended for over-the-counter (OTC) use by adults age 18 and over who have not previously received a sleep apnea diagnosis and is not intended to diagnose, treat, or aid in the management of sleep apnea. The absence of a notification is not intended to indicate the absence of sleep apnea.
Product codes
QZW
Device Description
The Sleep Apnea Notification Feature (SANF) is an over-the-counter mobile medical application (MMA) intended to identify patterns of breathing disturbances suggestive of moderate-to-severe sleep apnea and provide a notification to the user. SANF is intended to run on compatible iOS (e.g. iPhone, iPad) and Apple Watch platforms. Users set up SANF and view their health data on the iOS platform. Prior to use, users must undergo educational onboarding. SANF uses accelerometer sensor data collected by the Apple Watch to calculate breathing disturbance values while a user is asleep. Breathing disturbances describe transient changes in breathing patterns, such as temporary breathing interruptions.
Breathing disturbance data is analyzed in discrete, consecutive 30-day evaluation windows, If patterns consistent with moderate-to-severe sleep apnea are identified within the 30-day evaluation window, the user is notified. SANF provides visualizations depicting the user's breathing disturbance data over various time scales. SANF is not intended to provide instantaneous measurements. Instead, once activated, SANF runs opportunistically in the background receiving signals from Apple Watch sensors for processing.
Mentions image processing
Not Found
Mentions AI, DNN, or ML
SANF includes a deep learning algorithm to identify breathing disturbances using accelerometer sensor data from Apple Watch.
Input Imaging Modality
Not Found
Anatomical Site
Not Found
Indicated Patient Age Range
adults age 18 and over
Intended User / Care Setting
Over-the-counter (OTC) use
Description of the training set, sample size, data source, and annotation protocol
The model was trained on the Training set, with the Validation set used for early stopping and threshold selection. The algorithm development dataset included over 11,000 nights of concurrent reference and watch sensor data. The distribution of sleep apnea classifications in this dataset was broad and spanned all four clinically defined categories of sleep apnea: normal (AHI 0 to 30). Data from the studies was pooled and split into four sets: Training, Validation, Test, and Sequestration. The development data included a diverse group of subjects with respect to demographic factors (e.g., age, AHI, race, ethnicity, and BMI) representative of the intended use population.
Description of the test set, sample size, data source, and annotation protocol
The model was then evaluated on the Test set at regular intervals during model development was complete and the model was locked, it was evaluated on the Sequestration set as a last test to ensure it had not been over-fit to the training data. This process ensured no subject overlap and matching distributions of sex, age, BMI, and disease severity.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
The performance of the Sleep Apnea Notification Feature was validated in a prospective, nonsignificant risk study enrolling 1,499 subjects from several sites across the United States. The purpose of the study was to evaluate the performance of SANF using the Nox T3s home sleep apnea testing (HSAT) device (K192469) as a reference device. The study enrolled subjects across the spectrum of sleep apnea severity classifications, with a broad distribution across each of the following AHI categories using the "4%" hypopnea scoring rule: 559 normal subjects (AHI = 30), plus 161 subjects with missing HSAT reference. Subjects were also enrolled based across a broad range of demographic factors, including enrollment targets for age, sex, BMI, skin tone, race, and ethnicity subgroups to ensure the study population was representative of the intended user population.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
The sensitivity of notifications for subjects with moderate-to-severe sleep apnea (AHI >= 15) was 66.3%; 95% Cl [62.2%, 70.3%]. The specificity of the notifications for those with normal-to-mild sleep apnea (AHI
N/A
0
Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food & 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.
September 13, 2024
Apple Inc. Lynda Ikejimba Principal Regulatory Affairs Associate One Apple Park Way Cupertino, California 95014
Re: K240929
Trade/Device Name: Sleep Apnea Notification Feature (SANF) Regulation Number: 21 CFR 868.2378 Regulation Name: Over-the-counter device to assess risk of sleep apnea Regulatory Class: Class II Product Code: QZW Dated: April 4, 2024 Received: April 4, 2024
Dear Lynda Ikejimba:
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 (the Act) that do not require approval of a premarket approval application (PMA). You may, 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 available 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.
FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP) titled "SLEEP APNEA NOTIFICATION FEATURE (SANF) PREDETERMINED CHANGE
1
CONTROL PLAN" version 1.0. Under section 515C(b)(1) of the Act, a new premarket notification is not required for a change to a device cleared under section 510(k) of the Act, if such change is consistent with an established PCCP granted pursuant to section 515C(b)(2) of the Act. Under 21 CFR 807.81(a)(3), a new premarket notification is required if there is a major change or modification in the intended use of a device, or if there is a change or modification in a device that could significantly affect the safety or effectiveness of the device, e.g., a significant change or modification in design, material, chemical composition, energy source, or manufacturing process. Accordingly, if deviations from the established PCCP result in a major change or modification in the intended use of the device, or result in a change or modification in the device that could significantly affect the safety or effectiveness of the a new premarket notification would be required consistent with section 515C(b)(1) of the Act and 21 CFR 807.81(a)(3). Failure to submit such a premarket submission would constitute adulteration and misbranding under sections 501(f)(1)(B) and 502(o) of the Act, respectively.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review. the OS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
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 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 Part 803) for devices or postmarketing safety reporting (21 CFR Part 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 (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rue"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
2
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Rachana Visaria -S
Rachana Visaria, Ph.D. Assistant Director DHT1C: Division of Anesthesia. Respiratory, and Sleep Devices OHT1: Office of Ophthalmic, Anesthesia, Respiratory, ENT, and Dental Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
3
Indications for Use
Submission Number (if known)
K240929 Device Name
Sleep Apnea Notification Feature (SANF)
Indications for Use (Describe)
The Sleep Apnea Notification Feature (SANF) is a software-only mobile medical application that analyzes Apple Watch sensor data to identify patterns of breathing disturbances suggestive of moderate-to-severe sleep apnea and provides a notification to the user. This feature is intended for over-the-counter (OTC) use by adults age 18 and over who have not previously received a sleep apnea diagnosis and is not intended to diagnose, treat, or aid in the management of sleep apnea. The absence of a notification is not intended to indicate the absence of sleep apnea.
Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
X Over-The-Counter Use (21 CFR 801 Subpart C)
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510(k) Summary
This summary of 5 l 0(k) safety and effectiveness information is submitted in accordance with the requirements of 21 CFR §807.92:
1. Submitter
| Applicant | Apple Inc.
One Apple Park Way
Cupertino, CA 95014 |
|-----------------------------|----------------------------------------------------------------------------------------------------|
| Submission
Correspondent | Lynda Ikejimba, PhD
Regulatory Affairs
Phone: (669) 227-8858
Email: lc_ikejimba@apple.com |
| Secondary
Correspondent | Kevin Go
Regulatory Affairs
Phone: (669) 225-1032
Email: kevin_f_go@apple.com |
| Date Prepared | Sept 13, 2024 |
2. Device Names and Classifications
Subject Device:
| Name of Device | Sleep Apnea Notification Feature (SANF) |
|---|---|
| Classification Name | Over-the-counter device to assess risk of sleep apnea, 21 CFR |
| 868.2378 | |
| Regulatory Class | Class II |
| Product Code | QZW |
| 510(k) Review Panel | Anesthesiology |
3. Predicate Device
| Predicate | Value |
|---|---|
| Manufacturer | Samsung Electronics Co., Ltd |
| Trade Name | Sleep Apnea Feature |
| 510(k) | DEN230041 |
5
4. Device Description
The Sleep Apnea Notification Feature (SANF) is an over-the-counter mobile medical application (MMA) intended to identify patterns of breathing disturbances suggestive of moderate-to-severe sleep apnea and provide a notification to the user. SANF is intended to run on compatible iOS (e.g. iPhone, iPad) and Apple Watch platforms. Users set up SANF and view their health data on the iOS platform. Prior to use, users must undergo educational onboarding. SANF uses accelerometer sensor data collected by the Apple Watch to calculate breathing disturbance values while a user is asleep. Breathing disturbances describe transient changes in breathing patterns, such as temporary breathing interruptions.
Breathing disturbance data is analyzed in discrete, consecutive 30-day evaluation windows, If patterns consistent with moderate-to-severe sleep apnea are identified within the 30-day evaluation window, the user is notified. SANF provides visualizations depicting the user's breathing disturbance data over various time scales. SANF is not intended to provide instantaneous measurements. Instead, once activated, SANF runs opportunistically in the background receiving signals from Apple Watch sensors for processing.
5. Indications for Use
The Sleep Apnea Notification Feature (SANF) is a software-only mobile medical application that analyzes Apple Watch sensor data to identify patterns of breathing disturbances suggestive of moderate-to-severe sleep apnea and provides a notification to the user. This feature is intended for over-the-counter (OTC) use by adults age 18 and over who have not previously received a sleep apnea diagnosis and is not intended to diagnose, treat, or aid in the management of sleep apnea. The absence of a notification is not intended to indicate the absence of sleep apnea.
6. Comparison with the Predicate Device
SANF and the predicate device (DEN230041) have the same intended use, technological characteristics, and principles of operation, and the difference in indications does not represent a new intended use. Both the subject and predicate devices are software-only mobile medical applications intended to detect signs of moderate-to-severe sleep apnea for individuals who have not been previously diagnosed with sleep apnea and are not intended to provide a standalone diagnosis.
The subject device contains some differences in technological characteristics:
- The subject device is compatible with Apple products (i.e., iOS device, Apple Watch), while ● the predicate is compatible with Samsung products (i.e., Galaxy Watch and Phone).
- . The subject device utilizes passive, opportunistic detection to monitor the user over a 30day period, and only alerts the user if it detects signs of sleep apnea. The predicate device provides an on-demand two-day assessment, and returns either a positive or negative finding to the user.
- . The subject device utilizes accelerometer sensor data while the predicate device utilizes blood oxygen sensor data.
The differences in technological characteristics described above do not raise new questions of safety or effectiveness. The differences can properly be evaluated through the special controls
6
established in 21 CFR 868.2378. The subject device has been appropriately verified and validated through non-clinical and clinical testing to ensure that the device is substantially equivalent to the predicate. A complete comparison of the subject and predicate device can be found in Table 1 below.
| Item | Subject Device
Sleep Apnea Notification Feature | Predicate Device
(DEN230041) |
|--------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Device Name | Sleep Apnea Notification Feature
(SANF) | Sleep Apnea Feature |
| Manufacturer | Apple Inc. | Samsung Electronics Co., Ltd |
| Regulation Number | 21 CFR 868.2378 | 21 CFR 868.2378 |
| Product Code | QZW | QZW |
| Regulation Name | Over-the-counter device to assess risk of sleep apnea | Over-the-counter device to assess risk of sleep apnea. |
| Device
Classification | Class II | Class II |
| OTC/Prescription | OTC | OTC |
| Intended Use | An over-the-counter device to assess
risk of sleep apnea intended to provide
a notification of the risk of sleep apnea
in users who have not been previously
diagnosed with sleep apnea. This
device uses software algorithms to
analyze input sensor signals and
provide a risk assessment for sleep
apnea. It is not intended to provide a
standalone diagnosis, replace traditional
methods of diagnosis (e.g.,
polysomnography), assist clinicians in
diagnosing sleep disorders, or be used
as an apnea monitor. | An over-the-counter device to assess
risk of sleep apnea is intended to
provide a notification of the risk of sleep
apnea in users who have not been
previously diagnosed with sleep apnea.
This device uses software algorithms to
analyze input sensor signals and
provide a risk assessment for sleep
apnea. It is not intended to provide a
standalone diagnosis, replace traditional
methods of diagnosis (e.g.,
polysomnography), assist clinicians in
diagnosing sleep disorders, or be used
as an apnea monitor. |
| Table 1 : SANF Comparison with the Predicate | ||
|---|---|---|
7
| Item | Subject Device
Sleep Apnea Notification Feature | Predicate Device
(DEN230041) |
|---------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Indications for Use | The Sleep Apnea Notification Feature
(SANF) is a software-only mobile
medical application that analyzes Apple
Watch sensor data to identify patterns
of breathing disturbances suggestive of
moderate-to-severe sleep apnea and
provides a notification to the user. This
feature is intended for over-the-counter
(OTC) use by adults age 18 and over
who have not previously received a
sleep apnea diagnosis and is not
intended to diagnose, treat, or aid in the
management of sleep apnea. The
absence of a notification is not intended
to indicate the absence of sleep apnea. | The Sleep Apnea Feature is an over-
the-counter (OTC) software-only,
mobile medical application operating on
a compatible Samsung Galaxy Watch
and Phone. This feature is intended to
detect signs of moderate to severe
obstructive sleep apnea in the form of
significant breathing disruptions in adult
users 22 years and older, over a two-
night monitoring period. It is intended
for on demand use. This feature is not
intended for users who have previously
been diagnosed with sleep apnea.
Users should not use this feature to
replace traditional methods of diagnosis
and treatment by a qualified clinician.
The data provided by this device is also
not intended to assist clinicians in
diagnosing sleep disorders. |
| Principle of
Operation | SANF uses software algorithms to
analyze input accelerometer sensor
signals and provide a risk assessment
for sleep apnea. | The Sleep Apnea Feature uses software
algorithms to analyze input blood
oxygen sensor signals and provide a
risk assessment for sleep apnea. |
| Overall Device
Design | A software-only device, and uses
software algorithms to analyze input
sensor signals from a general purpose
computing platform and provide a risk
assessment for sleep apnea.
Assessments are based on sensor data
collected over 30-day periods. The
device is intended to provide
opportunistic detection of sleep apnea,
such that after initial enrollment no user
interaction is required for the device to
perform as intended. | A software-only device, and uses
software algorithms to analyze input
sensor signals from a general purpose
computing platform and provide a risk
assessment for sleep apnea.
Assessments are based on sensor data
collected over a 2-day period. The
device is intended to provide on
demand assessments to detect signs of
sleep apnea, such that a user must
actively choose to initiate a monitoring
period. |
| Use Environment | Over-the-counter | Over-the-counter |
| Device Components | Software-only | Software-only |
| Device Input | Accelerometer data | Blood oxygen level (SpO2) data |
| Item | Subject Device
Sleep Apnea Notification Feature | Predicate Device
(DEN230041) |
| Clinical
Performance | The performance was optimized for
high specificity given SANF is designed
as an opportunistic detection feature
(i.e., passive, recurring).
Sensitivity: 66.3%
95% CI [62.2%, 70.3%]
Specificity: 98.5%
95% CI [98.0%, 99.0%] | Sensitivity: 82.7%
95% CI [76.7%, 87.6%]
Specificity: 87.7%
95% CI [83.1%, 91.4%] |
8
7. Summary of Non-Clinical Testing
Algorithm Development
SANF includes a deep learning algorithm to identify breathing disturbances using accelerometer sensor data from Apple Watch. The model was trained on Apple Watch accelerometer signals collected during sleep sessions with concurrent in-lab polysomnography (PSG) and Home Sleep Apnea Test (HSAT) reference recordings. The algorithm development dataset included over II,000 nights of concurrent reference and watch sensor data. The distribution of sleep apnea classifications in this dataset was broad and spanned all four clinically defined categories of sleep apnea: normal (AHI 0 to 30). For the purposes of algorithm development, data from the studies was pooled and split into four sets: Training, Validation, Test, and Sequestration. 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 Test set at regular intervals during model development was complete and the model was locked, it was evaluated on the Sequestration set as a last test to ensure it had not been over-fit to the training data. This process ensured no subject overlap and matching distributions of sex, age, BMI, and disease severity. The development data included a diverse group of subjects with respect to demographic factors (e.g., age, AHI, race, ethnicity, and BMI) representative of the intended use population.
Non-clinical Testing Summary
Apple conducted the necessary non-clinical testing on SANF with passing results supporting a determination of substantial equivalence. Non-clinical testing conducted included the following:
Software Verification and Validation
Software verification and validation was conducted in accordance with Apple's robust Quality Management System and documented to address the recommendations in FDA's 2023 Guidance, "Content of Premarket Submissions for Device Software Functions." SANF was determined to require a Basic Documentation Level. Apple's good software engineering practices, as demonstrated through the submission's documentation, supports a conclusion that SANF was appropriately designed, verified, and validated.
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Cybersecurity
Apple approach to cybersecurity aligns with FDA's 2023 Guidance, " Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions." The device also conforms to the cybersecurity requirements identified in Section 524B to the FD&C Act.
Human Factors Validation
The Sleep Apnea Notification Feature was found to be safe and effective as compared to the predicate for the intended users, uses, and use environments. This conclusion is supported by iterative human factors analyses and evaluations on the device, resulting design modifications and the analysis of the summative validation testing results as recommended by 2016 FDA Guidance , "Applying Human Factors and Usability Engineering to Medical Devices".
General Purpose Computing Platform Assessment
SANF is a software-only device available on compatible general purpose computing platforms (e.g. Apple Watch); therefore, medical device hardware testing is not applicable. However, as a multiple function device product, the impact of the general purpose computing platform on SANF was assessed per FDA's 2020 Guidance, "Multiple Function Device Products: Policy and Considerations" and determined to be acceptable. This is consistent with the impact assessment of other Apple medical device features made available on Apple Watch, such as the Irregular Rhythm Notification Feature (K231173) and the Atrial Fibrillation History Feature (K213971).
8. Summary of Clinical Testing
The performance of the Sleep Apnea Notification Feature was validated in a prospective, nonsignificant risk study enrolling 1,499 subjects from several sites across the United States. The purpose of the study was to evaluate the performance of SANF using the Nox T3s home sleep apnea testing (HSAT) device (K192469) as a reference device. The study enrolled subjects across the spectrum of sleep apnea severity classifications, with a broad distribution across each of the following AHI categories using the "4%" hypopnea scoring rule: 559 normal subjects (AHI