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It is a motor driven, indoor and outdoor transportation vehicle with the intended use to provide mobility to a disabled or elderly person limited to a seated position.

The Scooter (Models: R-100) is an indoor/outdoor electric scooter that is intended to be used by individuals that are able to walk, but suffer from mobility limitations. It has a base with aluminum alloy frame, two front wheels, two rear wheels, two anti-tip wheels, a seat, an adjustable steering column, a control panel, an electric motor, an electromagnetic brake, a rechargeable battery with an off-board charger. The movement of the scooter is controlled by the rider who operates the direction control lever, speed control switch and handle on the control panel. The device is installed with an electromagnetic brake that will engage automatically when the scooter is not in use and the brake cannot be used manually.

The provided document is a 510(k) premarket notification from the FDA for a scooter (motorized three-wheeled vehicle). It is not an AI/ML medical device submission. Therefore, the information required to address the acceptance criteria for an AI/ML device, such as acceptance criteria in terms of performance metrics (sensitivity, specificity, AUC), sample sizes for test/training sets, ground truth establishment by experts, adjudication methods, or MRMC studies, is not present in this document.

The document discusses the regulatory process for clearing a non-AI medical device and demonstrates its substantial equivalence to a predicate device based on non-clinical performance testing against established international standards for wheelchairs and scooters.

Here's a breakdown of why I cannot fulfill the request with the provided text:

• Device Type: The device is a "Scooter, Model: R-100," a motor-driven transportation vehicle, not an AI/ML-driven diagnostic or analytical tool.
• Study Type: The "study" refers to non-clinical performance tests conducted to verify compliance with standards and demonstrate substantial equivalence to a predicate device. There is no mention of clinical studies, AI algorithm performance evaluation, or human reader studies.
• Acceptance Criteria for AI: The concept of sensitivity, specificity, AUC, or other AI performance metrics, as well as the methodology for evaluating AI (e.g., test/training sets, ground truth, expert adjudication, MRMC) are completely absent because they are irrelevant to this type of device.
• Ground Truth: The "ground truth" for a physical device like a scooter is its physical performance and safety characteristics as measured against engineering standards (e.g., static stability, dynamic stability, brake effectiveness, speed, range, weight capacity). It's not a diagnostic "truth" established by experts.
• Sample Size: "Sample size" in this context would likely refer to the number of scooters tested, not data samples for an AI algorithm. This information is not explicitly provided, only that "Non clinical tests were conducted to verify that the proposed device met all design specifications."

To reiterate, the document contains no information that would allow me to populate the requested table or answer the questions related to AI/ML device acceptance criteria and study methodology.

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