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The device is intended for medical purposes to provide mobility to persons restricted to a seated position.

The KARMA Scooter KS747.2 is an indoor / outdoor Powered Scooter that is battery operated. It has a base with four-wheeled with a seat. The movement of the Scooter is controlled by the rider who uses hand controls located at the top of the steering column. The device can be disassembled for transport and is provided with an onboard battery charger.

This document describes a 510(k) submission for the KARMA Scooter, KS747.2, an electrical scooter. The information provided focuses on the device's substantial equivalence to a predicate device rather than presenting a performance study with specific acceptance criteria and performance metrics typically associated with AI/software devices. Therefore, much of the requested information regarding AI device evaluation cannot be extracted from this document.

Here's an analysis of the provided text in relation to your request:

1. A table of acceptance criteria and the reported device performance

The document does not provide a table of acceptance criteria for specific performance metrics (e.g., accuracy, sensitivity, specificity) of the KARMA Scooter. Instead, it relies on demonstrating substantial equivalence to a predicate device, the WELL SUCCESS A&I Scooter, SC-402 (K041193).

The "performance testing" mentioned is related to safety and electrical standards, not functional performance metrics in the way you might expect for an AI device.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not applicable and not provided in the document as it describes a hardware device submitting for substantial equivalence based on engineering and safety testing, not a clinical study or AI performance evaluation with a "test set" of data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not applicable and not provided. The "ground truth" for this device's submission is its adherence to established safety standards and its functional equivalence to a predicate device, not, for example, expert consensus on disease diagnosis which would be relevant for an AI system. The "experts" involved would likely be engineers, safety testers, and regulatory compliance specialists.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not applicable and not provided. Adjudication methods are typically used in clinical studies involving human interpretation or AI output, which is not the nature of this submission.

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

This information is not applicable and not provided. An MRMC study is relevant for evaluating the impact of AI assistance on human performance in diagnostic tasks. The KARMA Scooter is a mobility device, not a diagnostic AI system.

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

This information is not applicable and not provided. "Standalone performance" refers to the performance of an AI algorithm independent of human interaction. The KARMA Scooter is a physical device controlled by a human, not an algorithm, so this concept does not apply.

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

The "ground truth" implicitly used for this submission is:

• Adherence to recognized performance and safety standards: ANSI / RESNA WC/Vol.2-1998, CISPR 11: 1990, EN61000-3-2: 1995, IEC61000-3-3: 1995.
• Demonstration of equivalence in critical specifications and materials to the predicate device, WELL SUCCESS A&I Scooter, SC-402 (K041193), which itself would have met relevant standards and safety requirements. This involves direct comparison of specifications and material certifications (e.g., UL certification for electronic systems, SGS test for back upholstery ignition resistance).

8. The sample size for the training set

This information is not applicable and not provided. "Training set" refers to data used to train an AI model.

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

This information is not applicable and not provided. This concept is specific to AI/machine learning development.

In summary: The provided document is a 510(k) summary for a physical medical device (an electrical scooter). Its acceptance criteria are based on demonstrating substantial equivalence to an existing legally marketed predicate device and conformance to safety and performance standards. The study described focuses on these aspects rather than on the type of AI/software performance evaluation queries you've asked.

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