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510(k) Data Aggregation

    K Number
    K101859
    Date Cleared
    2010-10-13

    (103 days)

    Product Code
    Regulation Number
    890.3420
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    REL-k is a prosthetic knee, important element of a lower limb prosthesis, a medical device that is used to replace a missing or deformed limb in both static and dynamic deambulation functions

    Device Description

    The Rel-k is an artificial limb prosthesis indicated for individuals that have undergone a trans-femoral amputation. The Rel-k is intended to replace a missing or deformed limb and functions in both normal/standing (static) and dynamic walking. The Rel-k consists of: Pyramidal Head, Angular Sensor, Force sensor, Servo assisted Hydraulic Damper (MPC damper), Removable Battery and electronics compartment, Carbon Fiber Shell (outer casing), Attachment for a standard 30mm diameter tube.

    AI/ML Overview

    The provided 510(k) summary for the Rel-k Artificial Limb Prosthesis does not contain information about acceptance criteria or a study proving the device meets said criteria in the way typically associated with AI/software devices. This document is for a physical medical device (an artificial limb), not a software algorithm or AI model, hence the typical metrics for software performance (sensitivity, specificity, AUROC, etc.) are not applicable here.

    The 510(k) process for devices like the Rel-k focuses on demonstrating "substantial equivalence" to a predicate device, primarily through engineering principles, physical testing (e.g., fatigue, static load), material compatibility, and sometimes clinical performance in human use for the specific physical device.

    Therefore, many of the requested fields regarding AI/algorithm performance and ground truth establishment cannot be filled from this document.

    However, I can interpret the request in the context of the provided document by focusing on the "demonstration of substantial equivalence" which is the core of this type of 510(k).

    Here's an attempt to address the prompt based on the available information, noting where information is not present:


    Acceptance Criteria and Study for Rel-k Artificial Limb Prosthesis

    The provided 510(k) summary for the Rel-k Artificial Limb Prosthesis focuses on establishing substantial equivalence to a legally marketed predicate device (Otto Bock C-Leg, K991590), rather than defining and meeting specific, quantifiable acceptance criteria for an AI or software model. The "study" in this context refers to the comparison and analysis performed to demonstrate this equivalence.

    This device is a physical knee joint for a prosthetic limb, and the regulatory pathway does not involve the type of performance metrics, training sets, or expert adjudication typically associated with AI/ML diagnostic or prognostic devices.


    1. Table of Acceptance Criteria and Reported Device Performance

    Given this is a physical device submission focused on substantial equivalence, the "acceptance criteria" are implied by the features and performance of the predicate device, and the "reported device performance" is the demonstration that the Rel-k is comparable.

    Acceptance Criteria (Implied by Predicate)Reported Device Performance (Rel-k)
    Intended Use: Replace a missing or deformed limb for static and dynamic deambulation.Intended Use: "REL-k is a prosthetic knee, important element of a lower limb prosthesis, a medical device that is used to replace a missing or deformed limb in both static and dynamic deambulation functions." (Matches predicate's function).
    Technological Characteristics: Functionality comparable to Otto Bock C-Leg (3C100).Technological Characteristics: "The Rel-k is substantially equivalent to the Otto Bock C-Leg (C100)... Differences that exist... related to the technical specifications, physical appearance and design does not raise new questions of safety and effectiveness." (Demonstrated comparable technology.)
    Safety and Effectiveness: No new questions of safety or effectiveness compared to predicate.Safety and Effectiveness: "demonstrates that the Rel-k device is at least as safe and effective as the legally marketed Otto Bock C-Leg (C100) device." (Asserted and accepted by FDA through clearance.)

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

    • Sample Size for Test Set: Not applicable in the context of an AI/ML algorithm's test set. For a physical device submission, this would typically involve mechanical testing (e.g., fatigue, static load tests) on a specific number of manufactured units, or potentially a limited human factors or clinical study if new questions of safety/effectiveness arose. This document does not detail specific physical testing numbers.
    • Data Provenance: Not applicable for AI/ML data provenance. Any testing data would have been generated in a lab setting, or potentially from a limited clinical trial (though none is explicitly mentioned as part of the equivalence demonstration for this Class I device).

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

    • Number of Experts: Not applicable. Ground truth for an AI/ML model.
    • Qualifications of Experts: Not applicable.

    4. Adjudication method for the test set

    • Adjudication Method: Not applicable.

    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

    • MRMC Study: No, this is not applicable as the device is a physical prosthetic component, not an AI-based diagnostic/assistant tool.

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

    • Standalone Performance: No, this is not applicable. The Rel-k is a physical device that functions in conjunction with a human wearer.

    7. The type of ground truth used

    • Type of Ground Truth: Not applicable for AI/ML ground truth. For a physical device, "ground truth" relates to engineered specifications, material properties, and the established performance profile of the predicate device against which the new device is compared. This would be established through engineering standards, mechanical tests, and potentially clinical evaluations of the predicate itself.

    8. The sample size for the training set

    • Sample Size for Training Set: Not applicable. This concept pertains to AI/ML models.

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

    • How Ground Truth for Training Set was Established: Not applicable.
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