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510(k) Data Aggregation

    K Number
    K970703

    Validate with FDA (Live)

    Device Name
    GALILEO HALLEY
    Date Cleared
    1997-05-19

    (82 days)

    Product Code
    Regulation Number
    882.1400
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Galiteo Halley Electroencephalograph is intended for use in acquiring and storing bioelectric signals produced by brain activity for the diagnosis and prognosis of neurological disease.

    Device Description

    The GALILEO HALLEY option is an intelligent patient box (fig. 1), able to work both in connection with a GALILEO station or as stand-alone. Therefore it includes the amplification, filtering, sampling, A/D conversion and data transmission functions, which in the other GALILEO stations are performed by the umplified patient box and by the GALILEO ACQ board. In the stand-alone mode HALLEY also memorizes the acquired data in GALILEO standard file format; in the other GALILEO stations the operative system of the PC itself accomplishes this operation.

    AI/ML Overview

    The ESAOTE Galileo Halley Biosound Essote (K970703) is an electroencephalograph (EEG) device intended for acquiring and storing bioelectric signals produced by brain activity for the diagnosis and prognosis of neurological disease.

    This submission is a 510(k) premarket notification, which means the device is seeking clearance based on substantial equivalence to a predicate device, rather than requiring extensive clinical trials for a new device. The provided document does not contain a study explicitly designed to "prove" the device meets acceptance criteria in the way a clinical trial would. Instead, the "study" is a comparison to predicate devices, demonstrating that the Galileo Halley has similar technical specifications and intended use, implying comparable safety and effectiveness.

    Here's an breakdown based on your request:

    1. Table of Acceptance Criteria and Reported Device Performance

    The acceptance criteria are implicitly defined by the technical specifications of the predicate devices, and the reported device performance indicates that the Galileo Halley meets or exceeds these.

    ItemPredicate Devices (Galileo Vega 24 EEG K923950 & Galileo Pleiade EEG K923894) Acceptance CriteriaGalileo Halley Performance
    Intended useEEG signal acquisitionEEG signal acquisition
    General system approachAmplification and pre-processing of EFG signalAmplification and pre-processing of EEG signal
    User input devicesSerial protocolSerial interface RS232
    User output devicesSerial protocolSerial interface RS232
    Operating channels3216/32 + 4
    A/D conversion12 bit12 bit
    Sampling rate512 s/sec/channel512 s/sec/channel
    Resolution0.5 $\mu$V/bit0.5 $\mu$V/bit
    CMRR>90dB>90dB (specifically >100dB in technical characteristics)
    IMRR>120 dB>120 dB
    Noise< 1.5 $\mu$Vpp< 1.5 $\mu$Vpp
    Low pass filters15-70 Notch15-30-60-90-120 Hz
    Time constant0.3-0.1-0.03-0.01 sec.0.3-0.1-0.03-0.01 sec.
    Power supplyfrom Galileo stationinternal (alkaline batteries)

    Note: The reported performance of the Galileo Halley often matches or surpasses the predicate devices, for example, offering a broader range of low-pass filters and multiple power supply options, and a higher CMRR.

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

    The document does not describe a "test set" in the context of clinical data. The "testing" for this 510(k) submission primarily consists of comparing the design and technical specifications of the Galileo Halley to legally marketed predicate devices. There is no mention of a specific number of cases or patients used for performance evaluation in a clinical setting.

    Data provenance is not applicable in the sense of patient data, as no such data is presented. The comparison is based on the design specifications of existing, cleared devices.

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

    Not applicable. This is a technical comparison for substantial equivalence, not a clinical study involving expert-established ground truth on patient data. The "ground truth" for this submission is the established performance and safety profile of the predicate devices.

    4. Adjudication method for the test set

    Not applicable. There is no test set in the clinical sense requiring an adjudication method.

    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 Galileo Halley is an EEG acquisition and storage device, not an AI-powered diagnostic tool requiring assessment of reader performance.

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

    The document states that the HALLEY can operate in a "stand-alone mode" where it stores acquired data on internal mass memory without being connected to a GALILEO station. This describes a functional mode of the device itself, not a separate standalone performance study of an algorithm. The standalone functionality refers to its ability to acquire and store EEG data independently, producing files indistinguishable and interchangeable with those from a GALILEO station. The performance of this standalone function is assessed by its technical specifications mirroring the connected mode.

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

    The "ground truth" for this 510(k) submission is the established safety and effectiveness of the identified predicate devices (Esaote Pleiade K923894 and Esaote Vega 24 K923950), based on their technical specifications, intended use, and general recognition as legally marketed devices.

    8. The sample size for the training set

    Not applicable. This device is not an algorithm that requires a training set.

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

    Not applicable, as there is no training set for an algorithm.

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