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To provide mobility to disabled or elderly persons limited to a seated position.

The FX 222-02 powered wheelchair is an indoor/outdoor powered wheelchair that is battery operated. The design of this wheelchair is basically similar to other powered wheelchairs that are already on the market.

This document is a 510(k) premarket notification for a powered wheelchair, the FX 222-02. It focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study of its performance against specific quantitative acceptance criteria in the manner one would expect for an AI/ML device.

Therefore, most of the requested information regarding acceptance criteria, study details, human reader performance, and ground truth establishment is not applicable to this type of regulatory submission. The product is a physical medical device, not an AI/ML algorithm.

Here's an analysis based on the document provided:

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

This document does not provide a table of acceptance criteria and reported device performance in the context of an AI/ML study. Instead, it states:

"There are minor differences in performance specifications of the powered wheelchairs, these differences do not alter the intended function and use of the device, nor do they raise any new questions pertaining to safety or effectiveness."

This indicates that the key "acceptance criterion" for this 510(k) submission is that the FX 222-02 powered wheelchair is substantially equivalent to the predicate device, Ruike 3421 (K070501), and that any "minor differences in performance specifications" do not negatively impact safety or effectiveness. Specific quantitative performance metrics are not detailed or compared in this summary.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not applicable. This is a physical medical device (powered wheelchair), not an AI/ML algorithm requiring a test set of data. The submission relies on a comparison to a predicate device and general safety/effectiveness considerations for mechanical devices.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. This is a physical medical device. Ground truth as typically defined for AI/ML algorithms (e.g., expert consensus on images or pathology results) is not relevant here.

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

Not applicable. This is a physical medical device.

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 is a physical medical device and does not involve AI assistance for human readers.

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

Not applicable. This is a physical medical device, not an algorithm.

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

Not applicable. For a physical device like a powered wheelchair, regulatory approval relies on general safety standards, mechanical performance tests (which are not detailed in this summary), and comparison to a legally marketed predicate device. "Ground truth" in the AI/ML context is not relevant.

8. The sample size for the training set

Not applicable. This is a physical medical device.

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

Not applicable. This is a physical medical device.

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