(123 days)
The MyOn HC™ Manual Wheelchair is intended to provide mobility to persons ages 12 and up (adolescents and adults) with a weight capacity of 220 & 290 lbs. depending on the seat width. The device is indicated to provide mobility to persons limited to a sitting position.
This Traditional [510(k)] submission is being supplied to the U.S. FDA to obtain authorization to market the MyOn HC™ Manual Wheelchair. The MyOn HC™ Manual Wheelchair is a foldable, manually operated fully adjustable lightweight wheelchair. It is indicated to provide mobility to persons which have limitations in mobility. It provides support and mobility to users that are seated in the wheelchair, for limited time up to permanent, full day usage. The design incorporates a horizontal folding mechanism connected to a left & right side frame on which many adjustments can be made to meet the individual user needs. The frame can be either equipped with swing in or swing out, detachable, riggings with an angle of 70°, 80° or the frame which has a fixed 80° front. It allows 5" of center of gravity (CG) adjustments and stepless backrest angle adjustments from -15° to + 15° which can be achieved whist the user is seated in the wheelchair. The subject device intended use is to provide mobility to persons ages 12 and up (adolescents and adults) with a weight capacity of 220 & 2901bs depending on the seat width. There is no prior submission for the subject device.
This document, K152536, describes the submission for the MyOn HC™ Manual Wheelchair and its substantial equivalence to a predicate device. However, this document does not contain information about a study proving the device meets specific acceptance criteria in the context of an AI/algorithm-based medical device.
The document details the regulatory approval process for a mechanical wheelchair, which involves non-clinical testing to demonstrate safety and performance against existing standards, rather than proving performance against specific acceptance criteria for an AI algorithm.
Therefore, many of the requested sections (sample size, expert qualifications, adjudication, MRMC studies, standalone performance, ground truth types for test and training sets) are not applicable or not present in this type of submission for a mechanical device.
Here's a breakdown of the available information:
1. Table of Acceptance Criteria and Reported Device Performance:
The document implicitly uses industry standards as "acceptance criteria" for mechanical performance and safety. It doesn't present a table with specific numerical acceptance criteria for a diagnostic/AI performance and corresponding reported device performance values in the way you'd expect for an AI device.
| Acceptance Criteria (Standards) | Reported Device Performance |
|---|---|
| ANSI / RESNA WC/Volume 2 2009, Section 1: Static Stability | Device testing demonstrated substantial equivalence to predicate. |
| ANSI / RESNA WC/Volume 1 2009, Section 5: Dimensions, Mass, Maneuvering Space | Device testing demonstrated substantial equivalence to predicate. |
| ANSI / RESNA WC/Volume 1 2009, Section 7: Seating and Wheel Dimensions | Device testing demonstrated substantial equivalence to predicate. |
| ANSI / RESNA WC/Volume 1 2009, Section 8: Static, Impact, and Fatigue Strengths | Device testing demonstrated substantial equivalence to predicate. |
| ANSI / RESNA WC/Volume 1 2009, Section 15: Information Disclosure, Documentation, Labeling | Device testing demonstrated substantial equivalence to predicate. |
| ANSI / RESNA WC/Volume 1 2009, Section 16: Resistance to Ignition of Upholstered Parts | Device testing demonstrated substantial equivalence to predicate. |
| CAL117:2013, Section 1: Flammability Testing | Device testing demonstrated substantial equivalence to predicate. |
| ISO 8191-1:1987 & 8191-2:1988: Flammability Testing | Device testing demonstrated substantial equivalence to predicate. |
2. Sample size used for the test set and the data provenance:
- Sample Size for Test Set: Not applicable in the context of an AI test set. Non-clinical physical testing of a mechanical wheelchair typically involves a small number of units to demonstrate compliance with standards. The document does not specify the number of units tested.
- Data Provenance: Not applicable in the context of clinical data for AI. The "data" here refers to the physical test results of the manufactured wheelchair.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Experts and Qualifications: Not applicable. Ground truth for a mechanical wheelchair's physical and safety performance is established by objective measurements against engineering standards, not by expert consensus in a medical diagnostic sense.
4. Adjudication method for the test set:
- Adjudication Method: Not applicable. Standardized testing for mechanical properties (e.g., weight capacity, stability, fatigue) has objective pass/fail criteria, not consensus-based 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:
- MRMC Study: No. This is a mechanical wheelchair, not an AI-assisted diagnostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Standalone Performance: No. This is not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- Ground Truth Type: Compliance with established engineering and safety standards (e.g., ANSI/RESNA, CAL117, ISO 8191). This is empirical and objective measurement against defined criteria, not medical ground truth like pathology.
8. The sample size for the training set:
- Training Set Sample Size: Not applicable. This is not an AI device trained on a dataset.
9. How the ground truth for the training set was established:
- Training Set Ground Truth: Not applicable.
In summary: The provided document is a 510(k) submission for a traditional mechanical medical device (a wheelchair). The regulatory review for such a device focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance and safety testing against established engineering standards. It does not involve AI algorithms, clinical study data, or human interpretation-based ground truth typical of AI/Machine Learning medical devices.
§ 890.3850 Mechanical wheelchair.
(a)
Identification. A mechanical wheelchair is a manually operated device with wheels that is intended for medical purposes to provide mobility to persons restricted to a sitting position.(b)
Classification. Class I (general controls).