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

The proposed device, Manual Wheelchair model XSG106A, is traditional manually operated, user propelled, manual, mechanical wheelchairs. The device can be foldable easily for transport. The main frame is made of magnesium alloy frame, the materials meet the standard of ASTM B107M-2012, and which has a seat base with four-wheeled with a back cover. Upon the outside of this framework, and to the rear, are assembled two axle plates, wheels are connected to the stainless steel axle receivers via stainless steel axles. On the front end of the frame are assembled two caster housings. Caster forks are mounted to these housings via steel axles. On the frame, upon the caster, two footplates are assembled for foot holding. Two armrests are mounted on the frame for user's arm holding. Two grips mounted on the top end of the frame with a brake, and another brake is designed under the seat base.

The provided text is a 510(k) summary for a Manual Wheelchair (Model XSG106A) and not an AI/Medical Imaging device. Therefore, the questions related to AI/Medical Imaging specific aspects such as "multi reader multi case (MRMC) comparative effectiveness study," "standalone (i.e. algorithm only without human-in-the loop performance)," "ground truth," expertise of readers, and training/test sets are not applicable to this document.

This submission focuses on demonstrating substantial equivalence to a legally marketed predicate device (K163352) primarily through non-clinical performance testing to relevant ISO standards for wheelchairs and biocompatibility standards.

Here's an analysis based on the provided document:

Acceptance Criteria and Device Performance

The acceptance criteria for this device are primarily met by demonstrating compliance with established international standards for wheelchairs and biocompatibility. The "Reported Device Performance" column essentially confirms that the proposed device complies with these standards.

Study Information (as applicable to a Mechanical Wheelchair 510(k))

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

   • The document does not explicitly state the "sample size" of devices tested. For mechanical devices like wheelchairs, testing is typically done on a representative number of units to ensure consistency and compliance with standards.
   • Data Provenance: The tests were non-clinical, conducted by the manufacturer, Jiangyin Newrise Medical Equipment Co., Ltd. The document indicates the company is based in Jiangyin City, Jiangsu Province, China. This suggests the testing was likely performed in China. The data would be considered prospective in the sense that the new device was built and then tested to these standards.

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

   • Not applicable. This is a mechanical device, not an AI/imaging device requiring expert interpretation for ground truth. Compliance is demonstrated through physical testing against engineering standards.

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

   • Not applicable. Adjudication methods are relevant for human interpretation of data, typically in clinical studies or for establishing ground truth in AI. For mechanical performance testing, the results are quantitative measures against pre-defined thresholds in the ISO standards, and do not involve human adjudication in this context.

4. 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 is not an AI/imaging device.

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

   • Not applicable. This is not an AI device.

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

   • The "ground truth" for this device's performance is defined by the measurement criteria and performance thresholds stipulated in the referenced ISO standards (e.g., maximum deflection under load, brake effectiveness measurements, stability angles). Compliance is determined by whether the device's measured performance falls within these pre-defined (objective) engineering limits.

7. The sample size for the training set:

   • Not applicable. This is not an AI device, so there is no training set in the machine learning sense. The "design" phase of the wheelchair could be seen as the "training" in an abstract engineering sense, where prototypes are iterated upon, but it's not a dataset size.

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

   • Not applicable. As above, no AI training set.

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