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510(k) Data Aggregation

    K Number
    K012825
    Device Name
    HEARTTRENDS
    Manufacturer
    Date Cleared
    2002-03-19

    (208 days)

    Product Code
    Regulation Number
    870.1425
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The HeartTrends™ software is intended for the analysis, summary and reporting of up to 3 channels of prerecorded ambulatory ECG data. reporting of up to 5 chainters of the MPW (Multipole Paramater Weighted) HRV.

    Device Description

    The HeartTrends™ software is employed as a measuring tool to present Heart Rate Variability (HRV) to qualified clinician review, edit and assessment. It provides measurements of the MPW (Multipole Paramater Weighted) HRV. The HeartTrends™ software is based on an algorithm, which is constructed The HeartTronos - sorvice, based on a physical-mathematical description of complex time series. The multipole method generates several parameters, multipoles, where every single one describes the HRV.

    AI/ML Overview

    The provided text is a 510(k) summary for the HeartTrends™ software (K012825). It focuses on the device's intended use, classification, and substantial equivalence to a predicate device. However, it does not contain information regarding acceptance criteria, specific performance study results, sample sizes for test or training sets, expert qualifications, or ground truth establishment.

    Therefore, I cannot provide a table of acceptance criteria and reported device performance or answer most of the specific questions about the study from the given text.

    Here is what can be extracted and what is missing:

    1. A table of acceptance criteria and the reported device performance

    • Missing. The document describes the device's function and intended use but does not provide any specific performance metrics or acceptance criteria for heart rate variability (HRV) analysis accuracy or other aspects of its function.

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Missing. No information on a test set, sample size, or data provenance is provided.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    • Missing. There is no mention of experts establishing ground truth for a test set.

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

    • Missing. No information on a test set or adjudication method is provided.

    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

    • Missing. The document does not describe any MRMC or comparative effectiveness study involving human readers or AI assistance. The HeartTrends™ software is presented as a "measuring tool to present Heart Rate Variability (HRV) to qualified clinician review, edit and assessment," implying it aids clinicians in their analysis rather than directly comparing human performance with and without AI assistance in an MRMC study.

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

    • Missing (implicitly stands alone as an analysis tool). The text states, "The HeartTrends™ software is intended for the analysis, summary and reporting of up to 3 channels of prerecorded ambulatory ECG data." This implies a standalone algorithmic analysis of ECG data to derive HRV parameters, which are then presented to a clinician. However, it doesn't describe a formal "standalone performance study" with metrics.

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

    • Missing. No specific ground truth type is mentioned. The device analyzes pre-recorded ambulatory ECG data to produce HRV parameters. Accuracy would likely be judged against established methods for calculating HRV from ECGs, but this is not detailed.

    8. The sample size for the training set

    • Missing. No information on a training set or its sample size is provided. The device is based on "an algorithm, which is constructed The HeartTronos - service, based on a physical-mathematical description of complex time series," suggesting a more model-driven approach than a purely data-driven machine learning one requiring a distinct "training set."

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

    • Missing. No training set or ground truth establishment for it is mentioned.
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