Search Results

The device 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.

The subject device, Powered Wheelchair, mainly powered by battery, motivated by DC motor, driven by user controlling joystick and adjusting speed. The Powered Wheelchairs consist of two foldable armrests, a backrest, a seat cushion, a safety belt, a foldable frame, two rear driving wheels with hub motor/electromagnetic brake assemblies, two pivoting casters, two Li-ion batteries, an off-board battery charger, a control panel, and an electric motor controller. The NXN20-209 Powered Wheelchair is intended to provide mobility to a disabled or elderly person limited to a seated position. The Powered Wheelchair has 7 inch front wheel and 12 inch rear tire. The motor of electric wheelchair is DC24V 200W; the battery is 24V 12AH, Li-ion battery; the charger is 24V/3A. Max. loading can not be over than 110Kgs. Max. distance of travel on the fully charged battery is 16.5 km and Max. speed forward is 6km/h. The braking time is about 2s, and the braking distance is less than or equal to 1.76m.

The provided text describes a 510(k) submission for a Powered Wheelchair (NXN20-209). This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than proving clinical effectiveness through a comparative study with a "human-in-the-loop" component as is common for AI/ML-driven diagnostics. The information provided is primarily related to engineering performance and safety standards for the physical device itself.

Therefore, the requested information regarding acceptance criteria and a study that proves the device meets the acceptance criteria, as phrased for AI/ML device performance (e.g., sample size for test set/training set, number of experts, adjudication methods, MRMC studies, standalone performance, ground truth establishment), is not applicable in the context of this traditional medical device submission.

The document states: "No clinical study implemented for the electric wheelchair." This confirms that the typical clinical performance studies asked for in your prompt were not conducted or required for this device's clearance.

Instead of AI/ML-specific performance criteria, the acceptance criteria for this powered wheelchair are based on adherence to recognized international standards for wheelchairs and a comparison of its physical and performance characteristics to a predicate device.

Here's a breakdown of what the document does provide in relation to acceptance criteria and performance:

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

The document includes two comparison tables (Table 1: General Comparison and Table 2: Performance Comparison) that demonstrate the similarity and conformance of the proposed device to a predicate device and relevant standards. While not "acceptance criteria" in the sense of a specific numerical threshold for a diagnostic outcome, these aspects represent the performance benchmarks the device successfully met.

Table 1 & 2 (summarized and adapted to your request format):

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

• Not Applicable. No human subjects "test set" was used for performance evaluation in the context of an AI/ML algorithm. The testing was non-clinical (bench and engineering tests) based on international standards for mechanical and electrical safety and performance of wheelchairs. The document does not specify a "sample size" for these non-clinical tests in the way one would for a clinical study. Data provenance is implied by the testing standards and the manufacturer's location (China), but not detailed as typical for clinical data.

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. Ground truth, in the AI/ML sense, is not established for this type of device. Performance is determined through objective, standardized engineering tests.

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

• Not Applicable. Not a clinical study requiring adjudication.

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 not an AI-assisted diagnostic or image analysis device, so MRMC studies are irrelevant.

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

• Not Applicable. This is a physical powered wheelchair, not an AI algorithm. Software verification and validation (standalone) was done for the device's control software, ensuring it functions correctly, but this is distinct from AI/ML performance.

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

• Not Applicable/Objective Standards. The "ground truth" for this device's performance is compliance with established international engineering and safety standards (e.g., ISO 7176 series, IEC 60601-1-2) which define objective, measurable criteria for stability, speed, braking, etc.

8. The sample size for the training set:

• Not Applicable. No AI/ML training set is mentioned or relevant for this device.

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

• Not Applicable. No AI/ML training set is mentioned or relevant for this device.

In summary: The provided document is for a traditional powered medical device, not an AI/ML-driven diagnostic or imaging device. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to documented compliance with relevant recognized industry standards (primarily ISO and IEC) through non-clinical testing, and demonstrated substantial equivalence to a predicate device.

Ask a specific question about this device