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510(k) Data Aggregation

    K Number
    K092335
    Date Cleared
    2010-04-09

    (248 days)

    Product Code
    Regulation Number
    868.1860
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    PEAK EXPIRATORY FLOW METER, KN-9710

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

    K-jump Health Co, Ltd. Peak Flow Meter, Model KN-9710, is intended for monitoring expiratory-breath function at home under direction of a physician or licensed health care professional. It measures the peak expiratory flow (PEF) and timed forced expiratory volumes over 1 second (FEV1). This device can be used from 6-year-old children to adult patients for monitoring and managing of chronic respiratory conditions, especially asthma and COPD.

    Device Description

    The Peak Flow Meter, KN-9710, uses hot wire on the thin film inside the air flow measurement tube. The hot wire will electrically heat up to a constant temperature. As air flow passes through the air flow measuring tube, the wires cool off, requiring extra electrical energy to heat up to the the constant temperature. The air flow sensor will instantly feed back a voltage to maintain temperature. And the proper proportion and evaluation of the peak flow rate and volume will be determined. The KN-9710 is a compact, small and light-weight designed portable handheld device that electronically measures the Peak Expiratory Flow (PEF) as will as the Forced Expiratory Volume in the first second of expiration (FEV1).

    AI/ML Overview

    Here's an analysis of the acceptance criteria and study detailed in the provided document:

    The document describes the K-jump Health Co., Ltd. Peak Flow Meter, Model KN-9710, intended for monitoring expiratory-breath function. The primary performance criteria revolve around the accuracy and precision of its measurements for Peak Expiratory Flow (PEF) and Forced Expiratory Volume in the first second (FEV1), as well as compliance with safety and biocompatibility standards.


    1. Table of Acceptance Criteria and Reported Device Performance

    Parameter/CharacteristicAcceptance Criteria (ATS 1994 update)Reported Device Performance
    Flow measuring accuracy± 10% or ± 20 l/min (whichever is greater for PEF)Well within required ATS accuracy specification
    Volume measuring accuracy± 5% or ± 0.1 L (whichever is greater for FEV1)Well within required ATS accuracy specification
    Interdevice variability(ATS 1994 update requirements for variability)Complies with all variability requirements
    Intradevice variability(ATS 1994 update requirements for variability)Complies with all variability requirements
    Electrical SafetyIEC 60601-1Complied
    Electromagnetic CompatibilityIEC 60601-1-2Complied
    BiocompatibilityISO 10993-1 (Cytotoxicity, Skin Sensitization, Skin Irritation)Complied (reports showed compliance with biological evaluation standard)

    Note: The document only explicitly states the predicate device's flow and volume accuracy comparison. For the subject device's performance, it broadly states "well within the required ATS (ATS 1994 update) accuracy specification" and "comply with all variability requirements" for both interdevice and intradevice variability. The specific numerical performance of the KN-9710 is not directly provided in the text beyond stating it met the ATS specifications.


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

    • Sample Size: The device performance was tested using 24 standard waveforms and 26 flow-time waveforms.
    • Data Provenance: The test was conducted at an independent laboratory, LDS Hospital (Salt Lake City, UT), U.S.A. The testing involved comparing the device's measurements against generated values from a precision waveform generator, rather than human patient data. Therefore, the data is prospective in the sense that the test was specifically designed and executed to evaluate the device against established waveforms.

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

    This section is not applicable as the ground truth was established by a precision waveform generator, not human experts. The reference standard was the generated values produced by this equipment, which is designed to simulate respiratory patterns with known, precise PEF and FEV1 values.


    4. Adjudication Method for the Test Set

    This section is not applicable. There was no human adjudication process since the comparison was between the device's output and the known, precisely generated values from a waveform generator.


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

    No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study typically involves human readers or operators assessing cases with and without AI assistance. This submission describes a standalone technical performance study of a measurement device.


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

    Yes, a standalone study was done. The description explicitly states: "The KN-9710 electronic peak flow meter was tested at an independent laboratory... The peak expiratory (PEF) and forced expiratory volume in one second (FEV1) measurement from the KN-9710 were compared against the generated values." This indicates the algorithm and hardware of the device were tested for their accuracy and precision in measuring PEF and FEV1 without human intervention impacting the measurement itself.


    7. The Type of Ground Truth Used

    The type of ground truth used was generated values from a precision waveform generator. This is a highly controlled, synthetic "ground truth" designed to emit specific, known respiratory flow and volume patterns.


    8. The Sample Size for the Training Set

    The document does not specify a sample size for a training set. This is typical for submissions of this nature, as the device is a measurement instrument calibrated against physical standards and engineering specifications, rather than a machine learning algorithm that requires a dataset for training. If the device's internal algorithms involve machine learning, the training set information is not provided in this document.


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

    This information is not applicable/not provided. As mentioned above, the document describes the testing and validation of the device, not its development or any potential machine learning training phase.

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