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KardiaMobile 6L is intended to record, store and two-channel electrocardiogram (ECG) rhythms. In single channel mode, KardiaMobile 6L can record Lead-I. In two channel mode, KardiaMobile 6L can record Lead-I and Lead-II simultaneously and derive Lead-III and unipolar limb leads aVR, aVF and aVL. KardiaMobile 6L also 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. KardiaMobile 6L 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.

KardiaMobile 6L is a trans-telephonic (transmission by smartphone) electrocardiogram (ECG) event recorder that records, stores, transfers, and analyzes single-channel or two channel ECG rhythm recordings. KardiaMobile 6L provides output of one or six ECG leads, including Lead I, Lead II, Lead III, aVL, aVR and aVF. The device utilizes the computing power of iOS-based or Android-based devices (referred to as "Mobile Computing Platforms" (MCP) within this 510(k)) to record and analyze ECG signals. KardiaMobile 6L consists of KardiaMobile 6L Hardware (portable small wireless hardware with electrodes) and the Kardia Core app. which is installed on an MCP (i.e., iOS or Android devices). KardiaMobile 6L Hardware uses Bluetooth to transmit the ECG signal from the electrodes to the Kardia Core app on the MCP, which then displays the recorded ECG on the MCP's screen. The device is intended to be used by patients with known or suspected heart conditions and health conscious individuals as well as by healthcare professionals (HCPs) who want to remotely monitor their patient's heart health. The device is available for Over-the-Counter (OTC) as well prescription use. The Kardia Core app provides the complete ECG recording and analysis workflow, from acquisition of the signal from the KardiaMobile 6L hardware, to the display of the ECG and analysis results, to printing of the ECG rhythm strip. The app utilizes KardiaAI (K181823, K201985) to provide ECG analysis, which includes the determinations of Normal Sinus Rhythm, Atrial Fibrillation, Bradycardia, Tachycardia, or Unclassified to OTC users and additionally, Sinus Rhythm determinations (Sinus Rhythm with Wide ORS, Sinus Rhythm with Supraventricular Ectopy, and Sinus Rhythm with Premature Ventricular Contractions) for prescription-use only users.

The document provided is a 510(k) summary for the AliveCor KardiaMobile 6L device. It describes the device, its intended use, and its substantial equivalence to a previously cleared predicate device.

Based on the provided information, the current submission (K220350) is for a minor modification (software reorganization and API addition) to an existing device (K210753, KardiaMobile 6L). Therefore, the study described here is primarily focused on demonstrating that these software changes do not adversely affect the device's safety or effectiveness as previously established.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states that the subject device (K220350) is being compared to its predicate (K210753). The performance criteria are implicitly met by demonstrating that the changes do not raise new questions of safety or effectiveness, as stated in the "Nonclinical Testing Summary" and "Conclusions" sections.

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

The document states: "No clinical testing was required for the minor changes made to the software." This implies that the current submission (K220350) did not involve a new clinical test set with human subjects to prove performance, but rather relied on nonclinical testing, specifically software verification activities.

Therefore, information on the sample size for a test set (e.g., number of ECGs, number of patients) or data provenance (country of origin, retrospective/prospective) directly related to a new clinical performance study for K220350 is not provided as it was explicitly deemed not required. The performance is being established by comparing to the predicate and ensuring the software changes did not introduce new risks. The previous predicate devices (K210753, K183319) would have had their own clinical data.

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

Not applicable, as no new clinical testing was performed for this specific submission (K220350). The performance claims are based on the substantial equivalence to the predicate, K210753, which would have established its own ground truth using experts.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

Not applicable, as no new clinical testing was performed for this specific submission (K220350).

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:

Not applicable. The document states "No clinical testing was required for the minor changes made to the software." This submission is not an MRMC study and does not evaluate AI assistance for human readers. It focuses on software reorganization and API addition.

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

The device description indicates that the Kardia Core app utilizes KardiaAI (K181823, K201985) to provide ECG analysis, detecting conditions like Normal Sinus Rhythm, Atrial Fibrillation, Bradycardia, Tachycardia, or Unclassified. This implies a standalone algorithmic analysis component. However, the current submission (K220350) primarily focuses on the software reorganization and API addition and explicitly states no new clinical testing was required. The performance of these AI determinations would have been established in the previous predicate clearances (K181823 and K201985), not in this particular submission.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

Not directly addressed for this specific submission (K220350), as no new clinical data was collected. For the underlying KardiaAI platform (K181823, K201985), the ground truth for ECG analysis typically involves expert consensus of cardiologists reviewing the ECGs.

8. The sample size for the training set:

The document does not provide details of the training set size, as this submission is not about training a new AI model but rather a software modification to an already cleared device that utilizes existing AI algorithms (KardiaAI K181823, K201985). The training data for those AI algorithms would have been described in their respective 510(k) submissions.

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

Not directly addressed for this specific submission (K220350), as it pertains to the training of the underlying KardiaAI algorithms (K181823, K201985) rather than the software reorganization. For such algorithms, ground truth for training is typically established by expert adjudication/consensus of ECG interpretations by qualified medical professionals (e.g., cardiologists).

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KardiaMobile 6L is intended to record, store and two-channel electrocardiogram (ECG) rhythms. In single channel mode, KardiaMobile 6L can record Lead-I. In two channel mode, KardiaMobile 6L can record Lead-I and Lead-II simultaneously and derive Lead-III and unipolar limb leads aVE. KardiaMobile 6L also 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. KardiaMobile 6L 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.

KardiaMobile 6L is a trans-telephonic (transmission by smartphone) electrocardiogram (ECG) event recorder that records, stores, transfers, and analyzes single-channel or two channel ECG rhythm recordings. KardiaMobile 6L provides output of one or six ECG leads, including Lead I, Lead II, Lead III, aVL, aVR and aVF. The device utilizes the computing power of iOS-based or Android-based devices (referred to as "Mobile Computing Platforms" (MCP) within this submission) to obtain and analyze ECG signals. KardiaMobile 6L consists of KardiaMobile 6L Hardware (portable small wireless hardware with electrodes) and the Kardia App, which is installed on an MCP (i.e., iOS or Android devices). KardiaMobile 6L hardware uses Bluetooth to transmit the ECG signal from the electrodes to the Kardia App on the MCP. KardiaMobile 6L displays thus record their ECG and additionally provides ECG analysis using the KardiaAI (K181823, K201985) ECG analysis suite, which includes the determinations of Atrial Fibrillation, Normal Sinus Rhythm, Bradycardia, Tachycardia, or Unclassified. The device is intended to be used by patients with known or suspected heart conditions and health conscious individuals as well as by healthcare professionals (HCPs) who want to remotely monitor their patient's heart health. Patients can forward the recorded ECG to their HCP, who can review the ECG for rhythm and to measure the QT interval. The device is available for Over-the-Counter (OTC) purchase and for purchase with a prescription. The Kardia App is also comes in an alternate variant, called the KardiaStation App that is exclusively used within hospitals and clinics; this app is identical to the Kardia App with the exception of incorporating patient administration workflows.

Here's a summary of the acceptance criteria and study details based on the provided text, focusing on the expanded use case of QT interval measurement for healthcare professionals:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document specifically addresses the expanded use case for healthcare professionals to measure the QT interval. It compares the KardiaMobile 6L's ability to measure QT intervals against a gold standard 12-lead diagnostic ECG device.

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

• Sample Size: 313 subjects.
• Data Provenance: Not explicitly stated regarding country of origin, but the study design suggests prospective data collection as ECG recordings were "taken comparison" and included "both healthy volunteers and patients suspected of long QT syndrome or other genetic heart disease."

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

• The document states that a "core lab used to provide precise QT measurements for Thorough QT studies was utilized to measure the QT and heart-rate corrected QTc in each ECGs."
• Number of Experts: Not specified.
• Qualifications of Experts: Implied expertise in QT measurement for Thorough QT studies, indicating highly specialized cardiac electrophysiology expertise.

4. Adjudication Method for the Test Set

• The document mentions that the core lab measured QT and QTc "in a randomized and blinded order, using standard measurement techniques." This suggests a robust, independent assessment, but a specific "adjudication method" (e.g., 2+1, 3+1) is not explicitly stated.

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

• No, a MRMC comparative effectiveness study was not explicitly described for the expanded QT interval measurement use. The study focused on the equivalence of QT measurements from the device compared to a gold standard, not on the improvement of human readers with AI assistance. The "human readers" in this context were the core lab experts establishing ground truth, not users of the device whose performance was being evaluated for improvement with AI.

6. Standalone (Algorithm Only) Performance

• No, an explicit standalone (algorithm only without human-in-the-loop performance) study for QT interval measurement was not described. The study validated that "a healthcare professional can review and measure the QT interval reliably using an ECG recorded using KardiaMobile 6L." While the device records the ECG, the measurement itself is performed by a human expert/core lab. The device's role here is data acquisition for human interpretation.
• It's important to note that the KardiaAI platform (K181823, K201985) does run algorithms for detecting Atrial Fibrillation, Normal Sinus Rhythm, Bradycardia, Tachycardia, or Unclassified rhythms, and these would have had standalone performance studies in their original clearances. However, for the expanded QT interval measurement claim, the study focuses on the reliability of the ECG recording for human measurement.

7. Type of Ground Truth Used

• Expert Consensus / Highly Specialized Core Lab Measurement: The QT and heart-rate corrected QTc measurements were performed by a "core lab used to provide precise QT measurements for Thorough QT studies." This represents a high-level, specialized form of expert consensus and measurement standard.

8. Sample Size for the Training Set

• Not provided. The document focuses on the clinical validation study for the QT interval measurement claim, which is a test set evaluation. Information about the training set for any underlying algorithms is not included in this 510(k) summary.

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

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

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The device is intended to measure blood pressure only, electrocardiogram (ECG) only or blood pressure and ECG simultaneously.

The device is a digital monitor intended for use in measuring blood pressure and pulse rate in adult population.

The device is intended to record, store, and transfer single-channel electrocardiogram (ECG) rhythms. The device also displays ECG rhythms and the output of ECG analysis including detecting the presence of atrial fibrillation, bradycardia, tachycardia and normal sinus rhythm, and others. The device 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 it is not intended for pediatric use.

The Omron Model BP7900 Blood Pressure Monitor + EKG ("BP7900") is a battery-powered automatic, non-invasive blood pressure (BP) and electrocardiography (ECG) measurement system intended for home use.

The BP7900 is intended for use in adult patients with arm circumferences between 17cm and 42cm. The device can be used with two different arm cuffs, the HEM-CS24-B and HEM-RML31-B which are adjustable to ranges of 17-22cm and 22-42cm, respectively. Other than the difference in circumference, the two cuffs function in the same manner.

The device inflates the arm cuff with an integral pump, then deflates the cuff via an electric valve. During inflation, the arm cuff pressure is monitored, and pulse waveform data is extracted. The extracted pulse waveform data is then analyzed by software which determines pulse rate, as well as systolic and diastolic blood pressure. The systolic and diastolic blood pressures are measured using the oscillometric method. The cuff pressure range is 0 to 299mmHg and the pulse rate range is 40 to 180 beats/minute. The results of the BP and pulse rate analysis are displayed on the front of the BP7900 for the user. In order to utilize the device, the user must also pair the BP7900 to a smartphone which employs the "Omron Connect" app. This app is intended to display trend graphs of measured systolic and diastolic blood pressure, and pulse rate. This app makes use of the cleared software of the AliveCor, Inc. KardiaMobile System (K191406) to analyze recorded ECGs and identify abnormal heart rhythms based upon the cleared algorithm parameters. Readings can be stored in the app for archiving and review by the user.

In addition to the BP measurement capabilities, the BP7900 also incorporates electrodes capable of gathering ECG data from the user. This can be done either concurrently with BP measurement, or as a separate function. To initiate the ECG, the user places a thumb on each of the right and left electrodes on the top face of the BP7900 and places two or more fingers in contact with the electrodes on the right and left side of the BP7900. The thumb electrodes measure at a rate of 300 samples/second as a single-lead ECG between left and right thumbs. The two remaining finger electrodes on the sides of the BP7900 are used for noise reduction purposes. The single-lead ECG data is transmitted via ultrasonic acoustics to the nearby smartphone with the cleared Kardia App (part of the KardiaMobile System, K191406) or Omron Connect App (Omron functional equivalent). The cleared app, which is incorporated from the KardiaMobile (K191406), allows the user to view their ECG and the results of analysis using the AliveCor's KardiaAI platform (K181823) which detects the presence of normal sinus rhythm, atrial fibrillation, bradycardia, tachycardia, and others.

The operation of the device is intended for home use. Functions and other features that are controlled by the end user include: applying the arm cuff to the arm, powering on/off the system, starting or stopping the blood pressure (BP) and pulse measurement cycle, and replacing the batteries as needed. Unlimited readings can be stored in the app for archive and review by the user.

The Omron Model BP7900 Blood Pressure Monitor + EKG received 510(k) clearance based on its substantial equivalence to two predicate devices: the Omron Model BP7900 Blood Pressure Monitor + EKG (K182579) and the AliveCor, Inc. KardiaMobile System (K191406). The primary change in the proposed device is a software update to the onboarding procedure for accessing ECG functionalities, aligning it with the secondary predicate.

Here's an analysis of the acceptance criteria and supporting studies based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The device is considered substantially equivalent, meaning its performance for key functionalities (blood pressure measurement, ECG recording, and ECG analysis) is expected to be as safe and effective as the predicate devices. The document explicitly states: "With respect to technological characteristics, there are no differences between the proposed and primary predicate devices with respect to the key functionalities blood pressure measurement, ECG recording, or ECG analysis."

The acceptance criteria are implicitly tied to the performance specifications of the predicate devices, particularly the primary predicate (K182579) which the proposed device largely mirrors in hardware and core functionality.

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

The document explicitly states: "No clinical testing was conducted in support of this 510(k) Premarket Notification."

Therefore, there is no information regarding a test set sample size or data provenance (country of origin, retrospective/prospective). The clearance relies on substantial equivalence to predicate devices, supported by nonclinical testing.

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

Since no clinical testing was conducted for this specific 510(k) submission, there were no experts used to establish ground truth for a new test set. The ECG analysis relies on the cleared AliveCor KardiaAI platform (K181823), which would have had its own validation studies involving experts. However, details of those studies are not part of this document.

4. Adjudication Method for the Test Set

Not applicable, as no new clinical test set was created or evaluated for this submission.

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

No MRMC study was conducted or reported in this 510(k) submission for the proposed device. The device's clearance is based on its substantial equivalence to existing devices and the fact that the changes made (primarily software for onboarding) do not raise new questions of safety or effectiveness. The ECG analysis is performed by the previously cleared KardiaAI platform, which likely had its own validation studies, but those are not detailed here for the proposed device itself.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study Was Done

The document does not detail any new standalone studies for the algorithms within the proposed device. The ECG analysis functionalities are provided by the "KardiaAI platform (K181823)," which was previously cleared. The blood pressure measurement is hardware-based (oscillometric method) with software analysis, and its performance is considered unchanged from the primary predicate. The nonclinical testing performed focused on verifying the software update related to onboarding procedures.

7. The Type of Ground Truth Used

For the current submission, no new ground truth was established as no new clinical studies were conducted. The device's performance is assumed to be equivalent to the predicate devices, which would have been validated against their respective ground truths (e.g., reference blood pressure measurements for the BP monitor, and expert-adjudicated ECGs for the KardiaMobile component).

8. The Sample Size for the Training Set

No information is provided regarding a training set for the proposed device, as no new clinical studies were conducted for this submission. The ECG analysis algorithms ("KardiaAI platform") had their own training sets, but details are not included here.

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

Not applicable to this submission, as no new training set or ground truth establishment relevant to the device's clearance were detailed. The KardiaAI platform's previous clearance (K181823) would contain this information.

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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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The device is intended to measure blood pressure only, electrocardiogram (ECG) only or blood pressure and ECG simultaneously.

The device is a digital monitor intended for use in measuring blood pressure and pulse rate in adult population. The device is intended to record, store, and transfer single-channel electrocardiogram (ECG) rhythms. The device also displays ECG rhythms and detects the presence of atrial fibrillation, bradycardia, tachycardia and normal sinus rhythm (when prescribed or used under the care of a physician). The device 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 it is not intended for pediatric use.

The Omron Model BP7900 Blood Pressure Monitor + EKG ("BP7900") is a battery-powered automatic, non-invasive blood pressure (BP) and electrocardiography (ECG) measurement system intended for home use.

The BP7900 is intended for use in adult patients with arm circumferences between 17cm and 42cm. The device can be used with two different arm cuffs, the HEM-CS24-B and HEM-RML31-B which are adjustable to ranges of 17-22cm and 22-42cm. respectively. Other than the difference in circumference, the two cuffs function in the same manner.

The device inflates the arm cuff with an integral pump, then deflates the cuff via an electric valve. During inflation, the arm cuff pressure is monitored, and pulse waveform data is extracted. The extracted pulse waveform data is then analyzed by software which determines pulse rate, as well as systolic and diastolic blood pressure. The systolic and diastolic blood pressures are measured using the oscillometric method. The cuff pressure range is 0 to 299mmHg and the pulse rate range is 40 to 180 beats/minute. The results of the BP and pulse rate analysis are displayed on the front of the BP7900 for the user. In order to utilize the device, the user must also pair the BP7900 to a smartphone which employs the "Omron connect" app. This app is intended to display trend graphs of measured systolic and diastolic blood pressure, and pulse rate. This app makes use of the cleared AliveCor Heart Monitor algorithm (K142743) to analyze recorded ECGs and identify abnormal heart rhythms based upon the cleared algorithm parameters. Readings can be stored in the app for archiving and review by the user.

In addition to the BP measurement capabilities, the BP7900 also incorporates electrodes capable of gathering ECG data from the user. This can be done either concurrently with BP measurement, or as a separate function. To initiate the ECG, the user places a thumb on each of the right and left electrodes on the top face of the BP7900 and places two or more fingers in contact with the electrodes on the right and left side of the BP7900. The thumb electrodes measure at a rate of 300 samples/second as a single-lead ECG between left and right thumbs. The two remaining finger electrodes on the sides of the BP7900 are used for noise reduction purposes. The single-lead ECG data is transmitted via ultrasonic acoustics to the nearby smartphone with the cleared AliveCor Heart Monitor or OMRON Connect App. These two applications are effectively the same, with the only difference being branding. The cleared app allows the user to view their ECG and the results of analysis using the AliveCor algorithm (cleared under K142743) which detects the presence of atrial fibrillation, and normal sinus rhythm.

The proposed BP7900 device utilizes the same ECG analysis algorithm including capabilities to detect the presence of bradycardia and tachycardia as that used in the AliveCor KardiaAI device cleared under K181823. All software V&V testing performed and submitted in this 510(k) utilized this algorithm.

The operation of the device is intended for home use. Functions and other features that are controlled by the end user include: applying the arm cuff to the arm, powering on/off the system, starting or stopping the blood pressure (BP) and pulse measurement cycle, and replacing the batteries as needed. Unlimited readings can be stored in the app for archiving and review by the user.

Here's a breakdown of the acceptance criteria and study information based on the provided text, focusing on the ECG analysis for atrial fibrillation, bradycardia, and tachycardia detection.

Part 1: Acceptance Criteria and Reported Device Performance

The acceptance criteria for the Omron Model BP7900 Blood Pressure Monitor + EKG primarily relate to its substantial equivalence to predicate devices for blood pressure measurement and ECG recording and analysis. For the ECG analysis specifically distinguishing atrial fibrillation, bradycardia, tachycardia, and normal sinus rhythm, the device leverages the algorithm from the AliveCor KardiaAI (K181823) and AliveCor Heart Monitor (K142743). Therefore, the device's performance for these ECG detections is implicitly expected to meet the established performance of these cleared devices.

Since specific numerical acceptance criteria or reported device performance for the ECG detection capabilities (sensitivity, specificity, accuracy) of the BP7900 itself are not explicitly provided in this document, we must infer that the substantial equivalence claim relies on the prior clearance of the AliveCor algorithms. The document states:

• "The proposed BP7900 device utilizes the same ECG analysis algorithm including capabilities to detect the presence of bradycardia and tachycardia as that used in the AliveCor KardiaAI device cleared under K181823." (Page 5)
• "The BP7900 employs the algorithm used for the AliveCor Heart Monitor. The BP7900 does not have an "Irregular Heartbeat Detection" feature which Omron BPMs normally have (estimated from measured BP pulse). Instead, it has an irregular pulse detection feature to identify possible AF, tachycardia which are estimated from ECG waveforms, not from blood pressure pulse." (Page 6)
• "Yes, includes ECG rhythm analysis for detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, and tachycardia (when prescribed or used under the care of a physician). Same as Heart Monitor. Bradycardia and Tachycardia detection same as reference device." (Page 10, "Irregular Heart Beat Detection" row)

Given this, the table below reflects an interpretation based on the provided text, implying that the acceptance for device performance is met by using a previously cleared and validated algorithm.

Part 2: Sample Size Used for the Test Set and Data Provenance

The provided document does not specify a sample size for an independent test set for the ECG detection performance of the BP7900 itself. The justification for the ECG detection capabilities (AF, bradycardia, tachycardia, normal sinus rhythm) relies entirely on the fact that the BP7900 utilizes the same algorithm as the previously cleared AliveCor Heart Monitor (K142743) and AliveCor KardiaAI (K181823) devices.

Therefore, any test set and data provenance information would refer to the studies originally conducted for the AliveCor devices, not a new, independent study for the BP7900's ECG detection performance. This document does not provide details of those original AliveCor studies.

Part 3: Number of Experts and Qualifications for Ground Truth

Similar to Part 2, the document does not provide details about the number and qualifications of experts specifically for the BP7900's ECG detection capabilities. This information would have been part of the original AliveCor submissions (K142743 and K181823). The BP7900's clearance for ECG detection is predicated on the re-use of these already cleared algorithms.

Part 4: Adjudication Method for the Test Set

As no specific new test set for the BP7900's ECG detection performance is detailed in this document, no adjudication method is described. This information would refer to the original AliveCor studies.

Part 5: Multi Reader Multi Case (MRMC) Comparative Effectiveness Study

The document does not mention an MRMC comparative effectiveness study comparing human readers with AI assistance versus without AI assistance specifically for the Omron BP7900. The device's ECG capabilities are based on a standalone AI algorithm (from AliveCor) that performs the detection. Whether the original AliveCor clearances involved such MRMC studies is not detailed here.

Part 6: Standalone Performance (Algorithm Only without Human-in-the-Loop Performance)

Yes, a standalone (algorithm only) performance was done, not for the BP7900 as a new, independent study, but through the pre-existing clearance of the AliveCor Heart Monitor (K142743) and AliveCor KardiaAI (K181823) algorithms. The BP7900 integrates these already validated algorithms. The document explicitly states: "The proposed BP7900 device utilizes the same ECG analysis algorithm including capabilities to detect the presence of bradycardia and tachycardia as that used in the AliveCor KardiaAI device cleared under K181823." (Page 5, and Page 18 under "Summary" and "Substantial Equivalence"). This phrasing indicates reliance on the standalone performance of those previously cleared algorithms.

Part 7: Type of Ground Truth Used

The document does not explicitly state the type of ground truth used for the original AliveCor algorithms. However, for ECG rhythm analysis, ground truth is typically established by:

• Expert Consensus: Multiple board-certified cardiologists or electrophysiologists independently reviewing ECG tracings and reaching a consensus diagnosis.
• Adjudicated Clinical Data: ECGs from patients with confirmed diagnoses based on a combination of clinical information, reference standard tests, and expert review.

Given the nature of ECG interpretation, expert consensus and/or adjudicated clinical data would be the most probable ground truth methods for the AliveCor algorithms.

Part 8: Sample Size for the Training Set

The document does not provide the sample size for the training set used to develop the AliveCor algorithms. This information would be specific to the original AliveCor submissions (K142743 and K181823).

Part 9: How the Ground Truth for the Training Set Was Established

The document does not provide details on how the ground truth for the training set of the AliveCor algorithms was established. As mentioned in Part 7, it would typically involve expert review and/or adjudicated clinical data from cardiologists or electrophysiologists.

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