(122 days)
The ECG app is a software-only mobile medical application intended for use with the Apple Watch to create, record, store, transfer, and display a single channel electrocardiogram (ECG) similar to a Lead I ECG. The ECG app determines the presence of atrial fibrillation (AFib), sinus rhythm, and high heart rate (no detected AF with heart rate 100-150 bpm) on a classifiable waveform. The ECG app is not recommended for users with other known arrhythmias.
The ECG app is intended for over-the-counter (OTC) use. The ECG data displayed by the ECG app is intended for informational use only. The user is not intended to interpret or take clinical action based on the device output without consultation of a qualified healthcare professional. The ECG waveform is meant to supplement rhythm classification for the purposes of discriminating AFib from sinus rhythm and is not intended to replace traditional methods of diagnosis or treatment.
The ECG app is not intended for use by people under 22 years old.
The ECG 2.0 app comprises a pair of mobile medical apps - one on Apple Watch and the other on the iPhone.
The ECG Watch app analyzes data collected by the integrated electrical sensors on a compatible Apple Watch to generate an ECG waveform similar to a Lead I. calculate average heart rate, and provide a rhythm classification to the user for a given 30 second session. When a user opens the ECG Watch app while wearing the Watch on one wrist, and places the finger of the opposite hand on the digital crown, they are completing the circuit across the heart which begins a recording session.
Once the recording session is complete, the ECG Watch app performs signal processing, feature extraction and rhythm classification to generate a session result.
The resulting classification and average heart rate for the session, along with educational information, will be displayed to the user within the ECG Watch app.
The ECG iPhone app contains the on-boarding and educational materials that a user must review prior to taking an ECG reading. The ECG iPhone app is included in the Health App, which allows users to store, manage, and share health and fitness data, and comes pre-installed on every iPhone. The ECG 2.0 app expands the classifiable heart range, introduces new classification results, and introduces minor, non-userfacing algorithm updates. These changes will be reflected in both the Apple Watch app, and also on the corresponding iPhone app within the Health App.
Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:
1. Table of acceptance criteria and the reported device performance
| Acceptance Criteria | Device Performance (ECG 2.0 App) |
|---|---|
| AFib Classification Sensitivity (HR 50-150 bpm) | 98.5% |
| Sinus Rhythm Classification Specificity (HR 50-150 bpm) | 99.3% |
| PQRST Waveform Visual Acceptability | 100% pass rating |
| R-wave Amplitude Assessment | 97.2% total pass rating |
2. Sample size used for the test set and the data provenance
- Sample size: Approximately 546 subjects.
- 305 subjects were in the Atrial Fibrillation cohort.
- 241 subjects were in the normal sinus rhythm cohort.
- Data provenance: Prospective, multi-center clinical trial. The country of origin is not explicitly stated, but it is a "multi-center" trial, implying diverse participant recruitment.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Number of experts: Not explicitly stated, but the ground truth was established by "a cardiologist." This implies at least one, likely a panel or multiple, to ensure robustness, though the exact number isn't quantified.
- Qualifications of experts: "Cardiologist." Years of experience are not specified.
4. Adjudication method for the test set
- The text states: "Rhythm classification of a 12-lead ECG by a cardiologist was compared to the rhythm classification of a simultaneously collected ECG from the ECG 2.0 app." This indicates that the cardiologist's interpretation of a 12-lead ECG served as the ground truth. It does not explicitly describe an adjudication method like 2+1 or 3+1 if multiple cardiologists were involved. It implies a single definitive classification by the cardiologist.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance
- No, a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with AI assistance versus without AI assistance was not conducted or reported in the provided text. The study focused on the standalone performance of the ECG 2.0 app against a cardiologist's interpretation.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
- Yes, a standalone performance study was done. The reported performance metrics (sensitivity, specificity, waveform acceptability) reflect the algorithm's direct classification capabilities compared to the ground truth established by a cardiologist. The device is intended for over-the-counter use, and its performance in classifying AFib and sinus rhythm was assessed directly.
7. The type of ground truth used
- The ground truth used was expert consensus / diagnosis from a cardiologist's interpretation of a 12-lead ECG.
8. The sample size for the training set
- The document does not explicitly state the sample size for the training set. It only mentions the test set (clinical trial of 546 subjects).
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 primarily focuses on the validation study. However, given that it states "Apple conducted database testing using a previously adjudicated dataset" for "ECG Database Testing per EC57," it is highly probable that the training data's ground truth was also established by expert cardiologists adjudicating ECGs in a similar manner to the test set, but this is not explicitly detailed for the training set.
§ 870.2345 Electrocardiograph software for over-the-counter use.
(a)
Identification. An electrocardiograph software device for over-the-counter use creates, analyzes, and displays electrocardiograph data and can provide information for identifying cardiac arrhythmias. 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 under anticipated conditions of use must demonstrate the following:
(i) The ability to obtain an electrocardiograph of sufficient quality for display and analysis; and
(ii) The performance characteristics of the detection algorithm as reported by sensitivity and either specificity or positive predictive value.
(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 validate detection algorithm performance using a previously adjudicated data set.
(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.