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The KardiaMobile System is intended to record, store and transfer single-channel electrocardiogram (ECG) rhythms. The KardiaMobile System also displays ECG rhythms and output of ECG analysis from AliveCor's KardiaAl platform including detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, and others. The KardiaMobile System is intended for use by healthcare professionals, patients with known or suspected heart conditions and health conscious individuals. The device has not been tested and is not intended for pediatric use.

The KardiaMobile System is a trans-telephonic (transmission by telephone) ECG (electrocardiogram) event recorder that records, stores and transfers single-channel electrocardiogram rhythms. The device utilizes the computing power of Apple iOS- and Google Android-based smartphones to obtain and analyze single-channel ECG. These smartphones are termed Mobile Computing Platforms (MCPs). The device consists of the hardware (that has the electrodes), and the Kardia phone app (installed on an MCP). The same software is implemented in the iOS and Android MCP. In either configuration, the same hardware is used to sense the ECG. The KardiaMobile Hardware transmits the ECG signal from the electrode to the Kardia phone app on the MCP to be analyzed and presented to the user. All ECGs are synced with the user's account.

The provided text describes the acceptance criteria and the study conducted for the KardiaMobile System, primarily focusing on proving that the device meets special controls for Electrocardiograph Software for Over-the-Counter Use, especially after the removal of a "clinician overread" function.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a direct table of numerical "acceptance criteria" (e.g., minimum sensitivity/specificity percentages) and corresponding "reported device performance" values for the AI algorithm suite (KardiaAI SaMD). Instead, it states that the performance characteristics (sensitivity and specificity) were "tested to meet the system requirements" against ANSI/AAMI EC57:2012 databases and AliveCor's proprietary databases.

However, the "Special Control" table implicitly functions as acceptance criteria for different aspects of the device's performance and the "Summary of Conformance" column indicates the reported performance/compliance.

Acceptance Criteria (Implicit from Special Controls) and Reported Device Performance (Summary of Conformance):

2. Sample Sizes Used for the Test Set and Data Provenance

• Sample Size for Algorithmic Performance (KardiaAI SaMD): The document states that the KardiaAI SaMD (K181823), leveraged by the KardiaMobile System for ECG analysis, was validated using "ANSI/AAMI EC57:2012 databases and AliveCor's proprietary databases." It also notes that these "validation datasets are representative of the patient population of the proposed device."
  • Specific sample sizes are NOT provided for these databases.
  • Data Provenance: Not explicitly stated regarding country of origin. The use of "ANSI/AAMI EC57:2012 databases" suggests a standardized, likely diverse, source, while "AliveCor's proprietary databases" could be from various global or specific regions. The document does not specify if the data was retrospective or prospective for the algorithmic validation, but typically such databases are compiled retrospectively.
• Sample Size for Human Factors and Usability Testing: Not explicitly stated, but it refers to "representative users."

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• For Algorithmic Performance (KardiaAI SaMD): The document states that the detection algorithm performance was validated using a "previously adjudicated data set" (Special Control 3) and mentions that for the primary predicate, the "overread unlock" mechanism involved review by a "board-certified cardiologist." However, it does not explicitly state the number or specific qualifications (e.g., years of experience) of experts used to establish the ground truth for the test sets used for the KardiaAI algorithm validation. Adjudicated data implies expert review, but details are absent.

4. Adjudication Method for the Test Set

• For Algorithmic Performance (KardiaAI SaMD): The document mentions "previously adjudicated data set." No specific adjudication method (e.g., 2+1, 3+1) is detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No MRMC comparative effectiveness study, comparing human readers with AI vs. without AI assistance, is mentioned. The focus of the changes and testing described is on the device's standalone performance and human factors/usability for over-the-counter use after removing the "overread" requirement.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes. The document explicitly states: "The KardiaMobile System leverages the KardiaAI SaMD (K181823) for ECG analysis. KardiaAI algorithm suite ECG detection algorithm outputs of Atrial Fibrillation, Normal, Bradycardia, Tachycardia, and Noise as well as the heart rate calculations were tested to meet the system requirements for sensitivity and specificity." This indicates that the core AI algorithm's performance was evaluated independently (without human-in-the-loop for its direct analytical output).

7. The Type of Ground Truth Used

• For Algorithmic Performance (KardiaAI SaMD): "Previously adjudicated data set." This typically implies expert consensus (e.g., cardiologists reviewing ECGs). It does not mention pathology or outcomes data as the ground truth directly for the AI algorithm's performance.

8. The Sample Size for the Training Set

• Not specified. The document focuses on the validation/test sets (ANSI/AAMI EC57:2012 and AliveCor's proprietary databases) for the KardiaAI algorithm. Information regarding the training set's size is not provided.

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

• Not specified. As the training set size itself is not mentioned, neither is the method for establishing its ground truth.

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The KardiaMobile System is intended to record, store and transfer single-channel electrocardiogram (ECG) rhythms. The KardiaMobile System also displays ECG rhythms and output of ECG analysis from AliveCor's KardiaAl platform including detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, and others (when prescribed or used under the care of a healthcare professional). The KardiaMobile System is intended for use by healthcare professionals, patients with known or suspected heart conditions and health conscious individuals. The device has not been tested and is not intended for pediatric use.

The KardiaMobile System is a trans-telephonic (transmission by telephone) ECG (electrocardiogram) event recorder that records, stores and transfers single-channel electrocardiogram rhythms. The device utilizes the computing power of Apple iOS- and Google Android-based smartphones to obtain and analyze single-channel ECG. These smartphones are termed Mobile Computing Platforms (MCPs). The device consists of the hardware (that has the electrodes), and the Kardia phone app (installed on an MCP). The same software is implemented in the iOS and Android MCP. In either configuration, the same hardware is used to sense the ECG. The KardiaMobile Hardware transmits the ECG signal from the electrode to the Kardia phone app on the MCP to be analyzed and presented to the user. All ECGs are synced with the user's account.

The provided documents describe the KardiaMobile System and its substantial equivalence to a predicate device. However, the specific acceptance criteria for the device's performance related to its AI algorithms (atrial fibrillation, normal sinus rhythm, tachycardia, bradycardia, and noise detection) and the detailed study that proves these criteria are met are NOT explicitly detailed within the provided text.

The document states:

• "The KardiaMobile System... displays ECG rhythms and output of ECG analysis from AliveCor's KardiaAI platform including detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, and others..."
• "Available Algorithms: Atrial Fibrillation, Noise Algorithm, Normal Sinus Rhythm, Tachycardia, Bradycardia (implements the same algorithms of the KardiaAI reference device, K181823)"
• "All necessary performance testing was conducted on the KardiaMobile System to support a determination of substantial equivalence to the predicate device. This testing included the following: - validation of KardiaAI integration"

While it confirms that "validation of KardiaAI integration" was part of the testing, it does not provide the specific acceptance criteria (e.g., sensitivity, specificity, accuracy targets for each rhythm detection) or the details of the study (sample size, ground truth establishment, expert qualifications, etc.) for the AI algorithms themselves.

Therefore, for aspects related to the performance of the AI algorithms, the requested information cannot be fully extracted from the provided text. The document focuses more on the substantial equivalence of the overall system (hardware and software integration) to a predicate device, rather than a detailed performance study for the AI algorithms against specific statistical targets.

However, based on the information provided for the overall system's substantial equivalence:

1. Table of acceptance criteria and the reported device performance:

The document does not provide a table with specific quantitative acceptance criteria (e.g., sensitivity, specificity, accuracy percentages) for the rhythm detection algorithms. Instead, the acceptance is based on the system demonstrating substantial equivalence to the predicate device (AliveCor Heart Monitor K142672) and the reference device's (KardiaAI K181823) algorithms, and meeting established specifications through nonclinical testing.

Reported Device Performance (General):

• Validation of KardiaAI integration: Performed.
• Verification of the device's specification: Performed.
• Testing to software level of concern requirements: Performed.
• Compliance with standards: ISO 10993-1:2009, IEC 60601-1:2012, IEC 60601-1-2:2007, IEC 60601-1-11:2015, IEC 60601-2-47:2012.
• Conclusion: "The collective results of the performance testing demonstrate that the KardiaMobile System meets the established specifications and complies with the aforementioned standards." and "The evaluation and testing results showed that differences between the subject and predicate device do not raise different questions of safety or effectiveness."

The following information applies to the overall system's validation and substantial equivalence as described, but not specifically to the detailed performance of the AI algorithms against quantifiable targets, which is not provided in the text.

2. Sample size used for the test set and the data provenance:

• Sample Size: Not specified in the provided documents. The text mentions "validation of KardiaAI integration" and "verification of the device's specification" but does not detail the size of the dataset used for these tests.
• Data Provenance: Not specified. It is not mentioned if the data was retrospective or prospective, or the country of origin.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not specified in the provided documents. The text does not detail the process of establishing ground truth for any test sets related to the AI algorithms.

4. Adjudication method for the test set:

• Not specified.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• A multi-reader multi-case (MRMC) comparative effectiveness study focusing on human readers improving with AI assistance is not described in the provided documents. The submission focuses on the substantial equivalence of the device, including its AI algorithms, rather than a comparative effectiveness study with human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• The document implies that the algorithms were evaluated independently as part of the "KardiaAI integration validation" and reference to "KardiaAI K181823". However, the specific details of such a standalone study (e.g., metrics, test set, ground truth) are not provided for the algorithms themselves. The overall device is described as having "output of ECG analysis from AliveCor's KardiaAI platform," suggesting that the algorithms perform analysis independently before being displayed to the user.

7. The type of ground truth used:

• Not specified in the provided documents.

8. The sample size for the training set:

• Not specified in the provided documents.

9. How the ground truth for the training set was established:

• Not specified in the provided documents.

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