(32 days)
The device is intended for medical purposes to provide mobility to persons restricted to a seated position.
The WU'S SCOOTER WT-M4A is an indoor / outdoor electric scooter that is battery operated. It has a base with four-wheeled with a seat, armrests, and a front basket. The movement of the scooter is controlled by the rider who uses hand controls located at the top of the steering column. The device can be disassembled for transport and is provided with an onboard battery charger.
The provided text is a 510(k) summary for the WU'S 4-WHEELED NEO SCOOTER, WT-M4A. It describes the device, its intended use, and its substantial equivalence to a predicate device. However, it does not describe a study that uses acceptance criteria for an AI/ML device. Instead, it outlines performance testing against established standards for mobility devices and compares the new device to a predicate device.
Therefore, I cannot directly extract the requested information regarding acceptance criteria and a study proving an AI/ML device meets them from the provided text. The questions seem to be tailored for AI/ML device submissions, which this document is not.
However, I can interpret the available information in the context of the general principles of device evaluation for substantial equivalence:
Interpretation of the provided information as an analogy to acceptance criteria for non-AI devices:
In this context, the "acceptance criteria" are not for an AI model's performance metrics (like sensitivity, specificity, etc.) but rather for the overall safety and effectiveness of the medical device (the scooter). The "study" is the performance testing and comparison to a predicate device to demonstrate substantial equivalence.
Here's how the provided information relates to the spirit of your request, even if not directly answering for an AI/ML device:
1. Table of "Acceptance Criteria" and Reported Device Performance (interpreted for a medical scooter):
| Acceptance Criteria Category (Implied by Regulation/Standards) | Reported Device Performance (WT-M4A) |
|---|---|
| Safety and Effectiveness | Demonstrated via compliance with EMC Report ANSI / RESNA WC/Vol.2-1998, CISPR 11: 1990, EN61000-3-2: 1995, IEC61000-3-3: 1995 standards. |
| Strength and Fatigue of Mainframes | Mainframes materials meet strength and fatigue tests; similar to predicate device WT-M4. |
| Electronic Systems Safety | Same suppliers as predicate device, UL certified for electronic controller, batteries, motors, and recharge. Ensures same safety level. |
| Weight Capability | 205 kgs (New device WT-M4A) |
| Cruising Range per Charge | 10-15 miles (New device WT-M4A). (Predicate WT-M4: 19 miles) |
| Incline Angle | 8 degrees (New device WT-M4A). (Predicate WT-M4: 12 degrees) |
| Components Similarity | Uses same suspension of cross brace, same size of wheels, same type of armrest, footplate, wheel lock, same warranty as predicate WT-M4. |
| Back Upholstery Materials | Same fabric as predicate device, passed resistance ignition test. |
| Intended Use | Same as predicate device: "to provide mobility to persons restricted to a seated position." |
2. Sample size used for the test set and the data provenance:
- Sample Size: Not explicitly stated as a number of individual scooters. The "test set" here refers to the device itself (WT-M4A) being tested against the stated standards and compared to the predicate device (WT-M4). Typically, this involves testing representative units.
- Data Provenance: The testing was conducted against international and national standards (ANSI / RESNA, CISPR, EN, IEC). The manufacturer is WU's TECH CO., LTD. in China (Taiwan). The report date is August 6, 2007. This suggests the testing data originates from the manufacturer's testing or accredited labs. It is a prospective evaluation of the new device's performance against established benchmarks.
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):
- This question is not applicable to this type of device submission. There is no "ground truth" to be established by experts in the sense of an AI/ML diagnostic task (e.g., diagnosing a condition from an image).
- Instead, the "ground truth" for a device like a scooter is defined by engineering specifications, safety standards, and performance test protocols established by regulatory bodies and industry associations (e.g., ANSI / RESNA). The "experts" would be the engineers and technicians conducting the tests according to these pre-defined standards.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- This question is not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical trials or expert review processes, particularly for AI/ML models where there might be disagreement on ground truth labeling.
- For a medical scooter, tests are typically objective and quantitative, conducted according to established procedures. The results are compared directly to the specified limits within the standards.
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:
- This question is not applicable. MRMC studies are specifically designed for evaluating the impact of AI assistance on human reader performance in diagnostic tasks (e.g., how AI helps radiologists detect diseases). This document pertains to a physical mobility device, not a diagnostic AI system.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- This question is not applicable. There is no "algorithm" in the sense of an AI/ML model for this device. The device itself is a standalone physical product. Its performance is measured directly against physical and electrical standards.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- As mentioned in point 3, the "ground truth" for this device is defined by established engineering and safety standards and performance test protocols (e.g., the safety limits for EMC, the strength requirements for materials, explicit performance criteria for weight capacity, cruising range, and incline angle). These are objective, measurable criteria, not subjective interpretations or clinical diagnoses.
8. The sample size for the training set:
- This question is not applicable. There is no "training set" for an AI/ML model described in this document. This refers to the data used to train an AI algorithm.
9. How the ground truth for the training set was established:
- This question is not applicable for the same reason as point 8.
§ 890.3800 Motorized three-wheeled vehicle.
(a)
Identification. A motorized three-wheeled vehicle is a gasoline-fueled or battery-powered device intended for medical purposes that is used for outside transportation by disabled persons.(b)
Classification. Class II (performance standards).