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510(k) Data Aggregation

    K Number
    K072630
    Device Name
    FORU, MODEL EQ30
    Manufacturer
    KWANG YANG MOTOR CO., LTD.
    Date Cleared
    2007-10-03

    (15 days)

    Product Code
    INI,89I
    Regulation Number
    890.3800
    Type
    Traditional
    Panel
    Physical Medicine
    Reference & Predicate Devices
    K051538
    Why did this record match?
    Device Name :

    FORU, MODEL EQ30

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

    The ForU EQ30 scooter is motor driven, indoor transportation vehicles with the intended use to provide mobility to disabled or elderly persons limited to a seated position.

    Device Description

    The ForU EQ30 scooter is an indoor/outdoor transportation vehicles which is battery operated. The movement of the scooter is controlled by a tiller handle and a thumb operated potentiometer throttle control lever to engage and disengage the scooter motion in both the forward and reverse directions.

    AI/ML Overview

    This document is a 510(k) premarket notification for a motorized scooter (ForU EQ30 scooter) and does not describe a clinical study or evaluation of an AI/ML device. Therefore, it does not contain the information requested in your prompt regarding acceptance criteria, study details, ground truth establishment, or multi-reader multi-case studies.

    The document primarily focuses on establishing "substantial equivalence" to a predicate device (AVANTICARE SA4022) by providing a comparison of specifications and intended use.

    Here's a breakdown of why this document cannot fulfill your request:

    • No AI/ML Device: The device is an "Electrical scooter," a physical motorized vehicle, not a software algorithm or AI/ML-driven medical device.
    • No Acceptance Criteria for an Algorithm: The acceptance criteria in this document are for a physical product, primarily focusing on safety and performance specifications (e.g., maximum loading, speed, braking distance) compared to a predicate device, rather than diagnostic accuracy or performance metrics of an algorithm.
    • No "Study" in the AI/ML Sense: The document refers to a "substantial equivalence comparison" which is a technical comparison of specifications, not a clinical study to prove the performance of an AI model against a ground truth.

    Therefore, I cannot extract the requested information like sample sizes for test sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, ground truth types, or training set details from this document.

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