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The Manual Wheelchair is intended for medical purposes to provide mobility to persons restricted to a sitting position.

The Manual Wheelchair is a wheeled personal mobility device that incorporates a seat-support system for a person with a disability or a person without the full capacity to walk designed to be manually propelled by the user while seated in the device or by an attendant. The occupant moves the wheelchair by rotating two handrims protruding from rear wheels. An attendant moves the device by pushing or pulling handles on the device. The device can be folded for transport. The device can be operated indoor or outdoor on dry, smooth surfaces composed of concrete, blacktop or asphalt under normal driving conditions. The subject manual wheelchair is a mechanical wheelchair with four wheels, including two front casters and two rear wheels, a frame made of carbon steel, a seat and a backrest made of oxford fabric, which is soft and water-resistant, two handles, armrests, handrims, foot pedals, legrest strap and seat belt. The subject manual wheelchair has a physical dimension of 1085mm × 700mm ×935mm (length × width × height). The device has a weight capacity of 100 kilograms, and its total mass is 17.3kg. The color is black.

This document describes the premarket notification (510(k)) for a Manual Wheelchair (Model: SYIV100-RLD-G01) seeking clearance from the U.S. Food and Drug Administration (FDA).

It's important to note that this is a Class I medical device (Mechanical Wheelchair, Product Code: IOR), which are generally considered low risk and do not require extensive clinical trials or complex AI performance criteria as seen with higher-class devices. The primary method for proving substantial equivalence for such devices is often through non-clinical performance testing and comparison to an existing predicate device.

Therefore, many of the typical "AI device" specific questions (like MRMC studies, training set details, or expert consensus for ground truth) are not applicable to this specific submission, as the device is not an AI-powered diagnostic or therapeutic tool. The "acceptance criteria" here refer to the device meeting established performance standards for manual wheelchairs, rather than AI performance metrics.

Here is the information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

For this manual wheelchair, the acceptance criteria are based on compliance with recognized performance and safety standards, and demonstrating that the proposed device performs "as well as" a legally marketed predicate device. The document does not present a formal "table of acceptance criteria and reported device performance" as one might see for an AI algorithm with metrics like sensitivity/specificity. Instead, it demonstrates compliance through adherence to ISO standards and a comparative analysis.

Acceptance Criteria (Implicit: Compliance with Standards and Predicate Equivalence)

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

• Test Set Sample Size: Not explicitly stated as a "sample size" in terms of number of patients or images, because this is a physical medical device. The "test set" here refers to the physical units of the manual wheelchair subjected to various engineering and biocompatibility tests. Typically, a small number of units (e.g., 1-3) are tested to demonstrate compliance with standards for Class I devices like this.
• Data Provenance: The tests are non-clinical (laboratory and engineering tests) conducted on the manufactured device. The geographic origin of the testing is not specified, but the manufacturer is based in China. The data would be considered prospective in the sense that the tests were performed specifically for this 510(k) submission.

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

• This is not applicable to this type of device submission. There is no "ground truth" established by human experts in the context of diagnostic or AI performance for a manual wheelchair. The "ground truth" for this device's performance is objective measurements against established engineering and biocompatibility standards.

4. Adjudication method for the test set

• This is not applicable. No adjudication method (like 2+1, 3+1 consensus) is relevant for non-clinical engineering and biocompatibility testing of a physical product like a manual wheelchair.

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 is not applicable. This is not an AI device or an imaging device requiring human reader studies.

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

• This is not applicable. This is not an AI algorithm.

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

• The "ground truth" for this device's performance is based on objective measurements and results from standardized non-clinical engineering tests (ISO 7176 series) and biocompatibility tests (ISO 10993 series). For example, a wheelchair either passes the static stability test at a certain angle or it doesn't; this is a measured outcome against a defined specification, not an expert opinion.

8. The sample size for the training set

• This is not applicable. This device is a physical product and does not involve AI/machine learning models that require training sets.

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

• This is not applicable. As it's not an AI device, there is no training set or associated ground truth establishment process.

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