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510(k) Data Aggregation

    K Number
    K971813
    Device Name
    EMBLA
    Manufacturer
    Date Cleared
    1998-01-16

    (245 days)

    Product Code
    Regulation Number
    882.1400
    Why did this record match?
    Reference Devices :

    K971867,K915856,K910771,K944833,K94603,K946094,K830295,K860456

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Embla is a polysomnographic system that is intended to record, display, and print EEG and other physiological information to clinicians/physicians. The device will be used in hospitals, institutions, sleep centers or clinics, or other test environments where patients require documentation of various sleep or other physiological disorders.

    Device Description

    The device is an EEG and physiological signs recorder. Embla is a polysomnographic system that is intended to record, display, and print EEG and other physiological information to EEG and other physicians. The device will be used in hospitals, institutions, sleep centers used in hospitals, institutions, environments where of various or clinics, of ocure documentation patients require doodaologic disorders. The Embla device is a totally digital recorder utilizing 16 channels of input Gata. The device is available in ambulatory as well as desktop configurations.

    AI/ML Overview

    I am sorry, but the provided text does not contain information about acceptance criteria, device performance results, or any study details that would allow me to populate the requested table and answer the specific questions about a device study.

    The document is a 510(k) summary for a device called "Embla," which is an electroencephalograph (EEG) and physiological signs recorder. It details the device's classification, proprietary name, substantial equivalence to predicate devices, description, intended use, and technological characteristics. It also includes the FDA's letter of substantial equivalence.

    There is no mention of:

    • Acceptance criteria for the device's performance.
    • Any specific study conducted to prove the device meets acceptance criteria.
    • Sample sizes for test or training sets.
    • Data provenance.
    • Number or qualifications of experts.
    • Adjudication methods.
    • Multi-reader multi-case studies or effect sizes.
    • Standalone algorithm performance.
    • Type of ground truth used.

    Therefore, I cannot fulfill your request with the given input.

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