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The device JWX-2 is a Power Assist Wheelchair Conversion Kit and suitable for the manual wheelchair users who are limited in their field of activities because of their physical conditions. The device can expand their field of activities by assisting their wheelchair operating force.

The device JWX-2 is an electric power assist unit for wheelchairs that turns a manual wheelchair into a power assisted wheelchair. The device supplies the assist power in response to the wheelchair handrim operating both push-and-brake forces in both directions. The user can operate the wheelchair just like a manual wheelchair with lighter hand force. The device consists of the left/ right power wheel units, battery charger. The power wheel units replace the original wheels of the manual wheelchair. Each power wheel unit has its own hand rim that incorporates the torque sensor which detects the user's operation force. Yamaha Ni-MH battery JWB2 and Yamaha Li-ion battery ESB1 can be used for the device. JWB2 is recharged with the charger JWC-2 and ESB1 is recharged with the charger ESC1. Both batteries can be charged in detached 'desktop' condition and the ESB1 can be charged also on the wheelchair condition. ESB1 does not supply the driving current during the charging to prevent the wheelchair to move. The assist power of the device is adjustable. The wheel locks of the manual wheelchair can be used to prevent the wheelchair from rolling and to keep the wheelchair complete stop like manual wheelchairs with the initial installation adjustment.

The provided text describes a 510(k) premarket notification for a medical device called JWX-2, a Power Assist Wheelchair Conversion Kit. It does not contain the information typically found in a clinical study report that would detail acceptance criteria and a study to prove they are met in the context of an AI/ML device.

This document is a regulatory submission demonstrating substantial equivalence to predicate devices, primarily through comparison of technical characteristics and adherence to recognized standards. It focuses on engineering and safety standards, rather than clinical performance metrics in the way an AI/ML device might be evaluated for diagnostic accuracy or clinical utility.

Therefore, most of the requested information regarding acceptance criteria, study design, sample sizes, expert ground truth, adjudication methods, MRMC studies, or standalone performance for an AI/ML device is not present in this document.

However, I can extract the following information which is relevant to device performance and regulatory standards:

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

The document presents a comparison table (Pages 6 and 7) of technical specifications between the JWX-2 and two predicate devices. These specifications implicitly serve as performance benchmarks or "acceptance criteria" for substantial equivalence. The "reported device performance" is the specification listed for the JWX-2.

• Dipped Vinyl Coated | - Stainless steel
• Dipped Vinyl Coated
• Removable rubber cover | **- Stainless steel
• Dipped Vinyl Coated** |
  | Certification | EN12184:2009 | EN12184:1999 | EN12184:2009 |

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. The document discusses device specifications and adherence to international standards, not a clinical test set with patient data for an AI/ML device. "Non-Clinical Testing" (Page 5) refers to tests against engineering standards, not patient data trials.

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 not an AI/ML device requiring expert-established ground truth from medical images or clinical records. The "ground truth" for this device would be its engineering specifications and performance against established safety and performance standards.

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

Not applicable. No clinical test set and no adjudication of expert opinions for an AI/ML 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 not an AI/ML device evaluated in an MRMC study.

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

Not applicable. This is a physical medical device (power assist wheelchair conversion kit), not a software algorithm.

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

The "ground truth" for this regulatory submission is adherence to established international engineering and safety standards for wheelchairs and electrical systems. For example, "ISO 7176-9: Climatic tests for electric wheelchairs," "ISO 7176-14: Power and control system for electrically powered wheelchairs and scooters – Requirements and methods," etc. These are objective engineering measurements and tests.

8. The sample size for the training set

Not applicable. This is not an AI/ML device with a training set.

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

Not applicable. No training set for this type of device.

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