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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 whole wheelchair can be folded by one button and it can be easily carried or rolled after folding. The seat cushion is detachable. The armrest can be flipped backward, which is convenient for the elderly to move. Users can drive the wheelchair by themselves through the control device. The wheelchair uses lithium batteries as its power source. The controls the drive left/right motor to realize the wheelchair forward, backward and turn functions. The frame of the device is carbon fiber. The front wheels are driven wheels suitable for rotation, acceleration, retrograde and other actions of the wheelchair. The front wheels movement will be achieved by thrust generated from the rear wheels. 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 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.

This document is an FDA 510(k) Premarket Notification for a Power Wheelchair (Model N6102). It aims to demonstrate substantial equivalence to a predicate device (K230964). Since this is a submission for a physical medical device (a power wheelchair) and not a software/AI-driven diagnostic or therapeutic device, the concepts of acceptance criteria, test sets, ground truth establishment, expert adjudication, MRMC studies, and separate training/test sets are not applicable in the context of typical AI/ML device evaluations.

The "acceptance criteria" and "study that proves the device meets the acceptance criteria" for a power wheelchair primarily revolve around compliance with recognized performance and safety standards (ISO 7176 series, IEC 60601-1-2, ISO 10993 series) and demonstrating that any differences from a predicate device do not raise new safety or effectiveness concerns.

Here's how to interpret the provided information in the context of device acceptance, organized to address your prompt's structure where applicable, but noting the non-applicability of certain AI/ML-specific terms:

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

The document provides a comparison of the proposed device against a predicate device, largely referencing compliance with international standards. The "acceptance criteria" are implied by these standards and the "reported device performance" is the statement of compliance or comparison to the predicate.

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

This information is not provided as it's not relevant for a direct testing of a physical device against standards (e.g., you test a specific number of manufactured units or prototypes for compliance, not a "data set"). The provenance isn't applicable in the same way either; the tests are performed on 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 is established by the specified ISO standards and validated test methods (e.g., a test rig for stability or braking) and direct measurements. It doesn't rely on expert consensus in the same way an AI diagnostic image reading might.

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

Not applicable. As above, the "truth" is determined by objective measurements against engineering standards, not through a consensus of human interpretative results.

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

Not applicable. This study is for a physical power wheelchair, not an AI software. There are no "human readers" or "AI assistance" in its intended function or evaluation.

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

Not applicable. This device does not contain an algorithm in this context. Its "performance" is mechanical and electrical, not computational.

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

The "ground truth" for this device's performance is derived from:

• International Standards: Primarily the ISO 7176 series, IEC 60601-1-2, and ISO 10993 series, which define objective test methods and acceptable performance limits for wheelchairs.
• Engineering Specifications: The design specifications for the device itself (e.g., max speed, loading weight, dimensions).
• Physical Testing: Direct physical measurements and tests on the device (e.g., dynamic stability tests, braking distance tests, obstacle climbing tests).

8. The sample size for the training set

Not applicable. This is a physical device, not an AI/ML model that requires a training set.

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

Not applicable. See point 8.

In summary, the "study" proving the device meets the "acceptance criteria" is a series of engineering tests and analyses demonstrating compliance with relevant international performance and safety standards for power wheelchairs, and a comparison to a legally marketed predicate device to demonstrate substantial equivalence. The differences noted (e.g., slightly different dimensions, braking distance, max loading weight, travel distance, obstacle climbing) are all deemed not to raise new safety or effectiveness concerns, with testing conducted to confirm compliance with the applicable standards even with these differences (e.g., "All safety and performance have been validated with the maximum rated weight dummy").

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