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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.

This product consists of frame, wheels, seat, armrest, lithium battery, motor and controller with a lightweight and compact design.The entire wheelchair can be disassembled, making it easy to carry. The wheelchair comes equipped with an electronically controlled rising seat that allows the user 280mm/11" of seat height adjustment using the joystick. The armrest can be flipped upside down, which is convenient for the elderly to move. Users can drive the wheelchair by themselves through the control device. The wheelchair uses lead-acid Battery as its power source. The controls the drive leftright motor to realize the wheelchair forward, backward and turn functions. The frame of the device is carbon steel. The front wheels suitable for rotation, acceleration, retrograde and other actions of the wheels movement will be achieved by thrust generated from the rear wheels are driving wheels to control the speed and direction. The wheels are Solid PU tires. When in use, the operator drives the motor of the rear wheel by operating the controller joystick to achieve the rear wheels movement. The DC brushless motor and brake system are fixed on the rear wheels. The max loading of the device is 136KG. Only for one person sit.

The provided text is a 510(k) summary for an electrically powered wheelchair. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study with specific acceptance criteria and detailed device performance metrics in the format requested.

Therefore, many of the requested elements of information, such as sample sizes, data provenance, expert qualifications, and MRMC study details, are not applicable or not available in this type of document, as it describes the testing and comparison of a physical medical device (a wheelchair) rather than a diagnostic AI algorithm.

However, I can extract the acceptance criteria as indicated by compliance with various ISO standards and the 'reported device performance' based on the comparison table and the general statements about meeting requirements.

Here's the closest representation of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not specify a distinct "test set" in terms of patient data or case numbers. Instead, it refers to performance and safety testing of the physical device according to various international standards (ISO). For tests involving a dummy, it mentions validation "with the maximum rated weight dummy." The number of devices tested is not explicitly stated.
• Data Provenance: The testing appears to have been conducted as part of the device development and verification process by the manufacturer in China. The specific location or date of individual tests are not detailed beyond the document preparation date (2025/2/26). The studies are inherently "prospective" in the sense that they are conducted to verify the new device's compliance.

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

• This section is not applicable. The device is an electrically powered wheelchair, not an AI diagnostic algorithm or system requiring expert-established ground truth from medical images or patient data. The "ground truth" for the device's performance is established by its compliance with engineering and safety standards, which are defined by standard bodies (like ISO) and regulatory bodies (like FDA), and verified through physical testing.

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

• This section is not applicable. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies to resolve discrepancies among multiple expert readers for diagnostic tasks. For a physical device like a wheelchair, performance is measured against objective engineering and safety standards, not subjective expert assessment of a diagnostic outcome.

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 section is not applicable. An MRMC study is relevant for evaluating the impact of AI on human reader performance in diagnostic tasks. This document is for a physical medical device (a wheelchair) and does not involve AI for diagnostic purposes or human readers.

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

• This section is not applicable. There is no AI algorithm being evaluated for standalone performance in this document. The device is a physical wheelchair.

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

• The "ground truth" in this context is defined by the technical specifications, requirements, and acceptable tolerances outlined in the referenced international standards (e.g., ISO 7176 series, ISO 10993 series, IEC 60601-1-2) which are based on engineering principles, safety considerations, and recognized testing methodologies. It's essentially engineering and safety standard compliance verified through objective physical testing.

8. The sample size for the training set:

• This information is not applicable as this document does not describe the development or testing of an AI model with a training set.

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

• This information is not applicable as this document does not describe the development or testing of an AI model with a training set.

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