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The intended use of the Pride Mobility Products Corporation Go Go Mini three wheel scooter, is to provide mobility to persons having limited walking capability, or simply to those who wish to ride a scooter for transportation purposes.

The Go Go Mini is a compact battery-operated three-wheel scooter having a programmable 45-amp "S" Drive Controller. Features include a removable molded plastic seat, a foldable tiller, and an off board charger. Additional safety features include electronic regenerative disc brakes, and rear anti-tip wheels. The Go Go Mini is designed for, but not limited to Pride Mobility Products Corp. providers / refailers and their consumers. The Go Go Mini is designed with ultimate safety, stability, performance, and portability in mind. The main feature of the Go Go Mini is that it can be disassembled into 4 parts: the rear section, the front section, the battery pack, and the seat. This allows for ease of use when traveling or storing the unit.

The provided document is a 510(k) summary for a medical device called the "Go Go Mini Power Wheelchair" (also referred to as "Go Go Mini / Three-wheel Power Scooter"). It does not include information about acceptance criteria or a study that proves the device meets specific acceptance criteria in the manner typically described for AI/ML-based medical devices or diagnostic tools.

Instead, this document details the substantial equivalence of the Go Go Mini to a predicate device (Pride Mobility Sunrunner TE-777, K923193) based on non-clinical testing and comparison of technological characteristics.

Therefore, I cannot provide the requested table and study details as they are not present in the provided text. The document explicitly states "Discussion of Clinical Testing Performed: N/A", which confirms that clinical trials (and thus, studies with detailed acceptance criteria, ground truth, expert adjudication, MRMC studies, or standalone performance) were not performed or are not reported in this submission for this device.

Here's what I can extract regarding the non-clinical testing performed, which is analogous to a "study" for this type of device, but without the detailed performance metrics you requested:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample size: Not specified. For mechanical device testing against standards, it usually involves testing a specific number of units of the device itself (e.g., one or more prototypes/production units) rather than a "test set" of data in the context of AI.
• Data provenance: The testing was non-clinical, meaning it likely involved laboratory or controlled environment testing of the physical device. Country of origin for the data is not specified, but the manufacturer is US-based (Exeter, PA). This would be considered prospective testing of the device.

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

• Not applicable. "Ground truth" in the context of device performance against engineering standards is usually established by the specifications of the standard itself and measurements taken by qualified testing technicians and engineers. Expert consensus or clinical adjudication is not typically relevant for this type of device submission.

4. Adjudication method for the test set:

• Not applicable. Compliance to standards is typically a pass/fail determination based on measurements and observations compared to the standard's requirements, not through an adjudication process in the clinical sense.

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:

• No. This is not an AI/ML device or a diagnostic tool involving human readers. The document explicitly states "Discussion of Clinical Testing Performed: N/A".

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

• No. This is a physical, battery-operated three-wheel scooter, not an algorithm.

7. The type of ground truth used:

• Compliance to established engineering and safety standards (e.g., ANSI/RESNA, CAL 117). The "ground truth" is the specifications and limits defined within these recognized standards.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device; therefore, there is no "training set."

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

• Not applicable.

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