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It 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 Solax Electric Scooter (Models: S204311M, S204161, S204143) is an indoor/outdoor electric scooter that is intended to be used by individuals that are able to walk, but suffer from mobility limitations. It has the following main components: two 6 inch solid front tires, two 7 inch solid rear tires, two anti-tip tires, control panel, steering handles, seat folding lever, backrest, arm rest, seat, steering column, seat frame, front/ rear covers, folding release lever, angle adjustment lever, height adjustment lock, carry handle, an off-board charger and aluminum alloy made frame, It is powered by two Li-ion DC rechargeable batteries with 18 km (on level surface) which maximum speed up to 6 km/hr. The movement of the scooter is controlled by the steering handles and control panel. The device is installed with an electromagnetic brake that will engage automatically when the scooter is not in use and the brake cannot be used manually.

This FDA 510(k) summary (K190737) describes the substantial equivalence of the Solax Electric Scooter to a previously cleared predicate device, rather than providing details of a study akin to those conducted for AI/ML-based medical devices. Therefore, much of the requested information regarding acceptance criteria, human reader studies, and ground truth establishment for AI systems is not applicable or present in this document.

However, I can extract information related to the performance testing and comparison to the predicate device, framing it as acceptance criteria and proof of meeting them within the context of a non-AI medical device.

Device Name: Solax Electric Scooter (Models: S204311M, S204161, S204143)
Intended Use: 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.

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

For a traditional medical device like this electric scooter, "acceptance criteria" are typically defined by performance standards (e.g., ISO standards) and by demonstrating equivalence to a predicate device. The "reported device performance" is the successful compliance with these standards and the demonstration that any differences from the predicate do not raise new safety or effectiveness concerns.

The remaining numbered points are primarily for AI/ML device studies and are not directly applicable to a traditional device 510(k) submission like this one, which relies on performance testing and substantial equivalence to a predicate.

2. Sample sized used for the test set and the data provenance:

• Sample Size: Not applicable in the context of an AI/ML test set. The study involves testing physical units of the scooter according to various ISO standards. The specific number of units tested is not detailed in this summary but would be determined by the requirements of each standard.
• Data Provenance: Not applicable. The "data" are results from physical performance and biocompatibility testing of the device itself, rather than a dataset of patient information. The testing would have been conducted by the manufacturer or a certified testing lab, likely in China, given the manufacturer's location. The testing is prospective in the sense that it's performed on the manufactured product to demonstrate compliance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. "Ground truth" in the AI/ML sense (e.g., expert annotation of medical images) is not relevant here. Compliance with ISO standards is determined by prescribed test methods and objective measurements.

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

• Not applicable. This is not a human reader study requiring adjudication. Test results are objectively measured against standard specifications.

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 device or an imaging device requiring human reader studies.

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

• Not applicable. This device does not use an algorithm in that capacity.

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

• Not applicable in the AI/ML sense. The "ground truth" for this device's performance is defined by the objective pass/fail criteria of the various ISO performance and safety standards, and the direct comparison of its physical and functional characteristics to the predicate device.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device that requires a training set.

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

• Not applicable.

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The Electric wheelchair (Model: S7110) is a motor driven, indoor transportation vehicle with the intended use to provide mobility to a disabled or elderly limited to a seated position.

Not Found

This document is a 510(k) clearance letter from the FDA for an "Electric Wheelchair (Model: S7110)". It confirms that the device is substantially equivalent to legally marketed predicate devices.

The letter does not contain information about acceptance criteria, a specific study proving device performance against acceptance criteria, sample sizes, data provenance, expert qualifications, adjudication methods, multi-reader multi-case studies, standalone algorithm performance, or ground truth details.

The document primarily addresses the regulatory approval process and includes the Indications for Use statement for the electric wheelchair.

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The device is a power wheelchair intended to provide mobility to persons restricted to a sitting position.

The Electric wheelchair (Model S7204, S7205) is a power wheelchair intended to provide mobility to persons restricted to a sitting position. The Electric wheelchair (Model S7204, S7205) is about 136 kg weight capacity. It is basic conventional rear wheels drive, rigid frame vehicle that are battery powered. It consists primarily of a welded-aluminum frames, sealed transaxle motors drive system, electromagnetic braking system, electric motor controller and Li-ion batteries with an off-board battery charger. It is powered by rechargeable batteries with 45 km which maximum speed up to 7 km/h. The controller with a joystick attaches to either armrest and allows the rider to control the movement and velocity of the powered wheelchair. When the joystick is released. the electromagnetic brake will be actuated and the power wheelchair is slow to stop. It consists of three parts which are chair part, control part and drive part. Overall it mainly has a basic aluminum alloy frame, two front wheels, two rear wheels, two anti-tip wheels, a seat, a footrest, an controller, an electric motor, an electromagnetic brake and a Lithium battery with an off-board charger. The result of "tiltover" tests performed laterally (12° ), posteriorly (16° ), and anteriorly (12° ) with a user of maximum allowable weight in the least stable configuration: No overturn performed laterally, posteriorly, and anteriorly with 136kg in the least stable configuration.

The provided text is a 510(k) summary for an Electric Wheelchair, Models: S7204, S7205. It describes the device, its intended use, and comparative testing against predicate devices to establish substantial equivalence.

However, the document does not describe an AI medical device or a study involving human readers or AI assistance. It focuses on the physical and functional characteristics of an electric wheelchair and its compliance with various ISO and IEC standards relevant to wheelchairs and medical electrical equipment.

Therefore, many of the requested criteria cannot be extracted from this document, as they pertain to AI/ML device performance and clinical studies involving expert readers, which are not present here.

Here's a breakdown based on the information available:

Acceptance Criteria and Device Performance Study (Electric Wheelchair)

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly list "acceptance criteria" in a typical table format for an AI device. Instead, it refers to compliance with various international standards for wheelchairs and medical electrical equipment. The "reported device performance" is mainly a comparison of the subject device's specifications against those of two predicate devices, with notations on substantial equivalence.

Key Performance & Safety Standards (implicit acceptance criteria by compliance):

2. Sample size used for the test set and the data provenance

Not applicable. The "test set" here refers to the device itself and components undergoing engineering and safety tests, not a dataset for an AI model. Testing was performed on the electric wheelchair models S7204 and S7205. The provenance of the data is from specific tests conducted by the manufacturer/laboratories against established international standards.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. This is not an AI/ML device requiring expert ground truth for a diagnostic or prognostic task. The "ground truth" is established by the specifications defined in the international standards (e.g., how to measure static stability, speed, brake performance).

4. Adjudication method for the test set

Not applicable. This concept typically applies to expert review of data for AI model training or evaluation, which is not relevant here. The evaluation is based on compliance of physical and functional tests with established 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

Not applicable. This is an electric wheelchair, not an AI-assisted diagnostic or prognostic device. No MRMC study or evaluation of human readers with/without AI assistance was performed.

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

Not applicable. This is an electric wheelchair. There is no standalone algorithm being evaluated.

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

For this device, the "ground truth" is defined by the objective performance criteria and methodologies outlined in the referenced ISO and IEC standards. For example, static stability is measured according to ISO 7176-1, brake performance according to ISO 7176-3, and biocompatibility according to ISO 10993. These are engineering and safety standards, not clinical ground truth of a diagnostic nature.

8. The sample size for the training set

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

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

Not applicable. This is not an AI/ML device.

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It 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.

Not Found

This document is a 510(k) clearance letter from the FDA for a Solax Electric Scooter, a motorized three-wheeled vehicle. It does not contain any information about an AI/ML-based medical device, its acceptance criteria, or performance study details.

Therefore, I cannot provide the requested information regarding acceptance criteria and performance study for an AI/ML device based on the provided text. The document is strictly about a physical mobility device.

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The Electric wheelchair is a motor driven transportation vehicle with the intended use to provide mobility to a disabled or elderly limited to a seated position.

The Electric wheelchair (Model S7012) is to provide mobility to adults, limited to a seated position that have capability to operate a few simple controls and the ability to control a powered wheelchair. The device and accessories (remote controller, AC power wire, charger, and battery) are reusable. The Electric wheelchair (Model S7012) is about 125 kg weight capacity and size is about 840mm x 640mm x 930mm if unfold and about 700mm x 640mm x 370mm if fold. It is basic conventional rear wheels drive, rigid frame vehicle that are battery powered. It consists primarily of a foldable welded-aluminum frames, sealed transaxle motors drive system, electromagnetic braking system, electric motor controller and Li-ion batteries with an off-board battery charger. It has some components as two front wheels, two rear wheels, two anti-tip wheels, a seat, a footrest, and has a remote for folding/unfolding the device. Its basic function is powered by rechargeable batteries with 15 km which has a maximum speed up to 6 km/h. The controller with a joystick attaches to either armrest and velocity of the powered wheelchair. When the joystick is released, the electromagnetic brake will be actuated and the power wheelchair is slow to stop. The joystick can move up and down, left and right. There is a speed button to adjust the speed, and the speed indicator can display the speed. In addition, there is a remote control to control the folding and unfolding of the device. And no any new features of the device.

The provided text is a 510(k) Summary for an Electric Wheelchair (Model: S7012). It focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific clinical studies against acceptance criteria in the manner one might expect for a novel AI/software as a medical device.

Therefore, the requested information regarding detailed acceptance criteria, study design for proving those criteria, sample size for test sets, expert involvement, adjudication methods, MRMC studies, standalone performance, training set details, and ground truth establishment does not apply in the context of this traditional medical device submission. The submission relies on adherence to established international standards for wheelchairs and a comparison of technical specifications to a predicate device.

However, I can extract the closest analogous information from the document:

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

The acceptance criteria are generally implied by conformity to the listed ISO and IEC standards and demonstrating substantial equivalence to the predicate device in terms of specifications. The "reported device performance" is given by the subject device's specifications.

2. Sample size used for the test set and the data provenance:

• Sample Size: Not applicable. The "tests" mentioned are conformity to international standards (e.g., ISO 7176 series, IEC 62304) for a physical device, not statistical performance evaluations against a test set of data. These standards typically involve testing a single or a small number of physical units to verify specifications and safety features.
• Data Provenance: Not applicable in the context of data used for statistical evaluation of a test set. The provenance of the tested device itself is Dongguan Prestige Sporting Goods Co., Ltd., China.

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 device is an electric wheelchair, not an AI/diagnostic device that generates an output needing expert "ground truth." The "truth" is established by direct physical measurement, engineering tests, and adherence to performance specifications outlined in the international standards cited (e.g., measuring speed, stability, brake effectiveness).

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

Not applicable for this type of device submission. Adjudication methods are typically used in clinical studies where expert consensus is needed to define a ground truth for a diagnostic outcome.

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. MRMC studies are specific to evaluating the effectiveness of AI-assisted diagnostic tools on human reader performance. This device is a physical mobility aid.

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

Not applicable. This device is a physical product (electric wheelchair), not an algorithm or AI system.

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

The "ground truth" for this device's performance relies on:

• Direct Physical Measurements: E.g., dimensions, weight, speed, range, turning radius.
• Engineered Safety Standards: Compliance with ISO 7176 series (static stability, dynamic stability, brakes, strength, climatic tests, EMC, etc.), IEC 62304 (software life-cycle), IEC 60601-1-6 (usability), IEC 62366 (usability engineering), and ISO 10993 series (biocompatibility).
• Comparison to a Predicate Device: Demonstrating that any differences in specifications do not raise new questions of safety or effectiveness.

8. The sample size for the training set:

Not applicable. This is not an AI/machine learning device.

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

Not applicable. This is not an AI/machine learning device.

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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 ZIPPY scooter consists of a retractable platform which connects the two front wheels and two rear wheels, an adjustable tiller, a lead acid battery with an off-board charger, a motor/electromagnetic brake assembly, a electric motor controller and a seat /backrest set. It can be retracted for transport in a car trunk.

The patient uses the tiller handle/handlebar for steering and a thumb operated potentiometer throttle control lever located at the top of the tiller to engage and disengage the scooter motion in both the forward and reverse directions. When the throttle control lever is released, the electromagnetic brake will be actuated and the scooter is slow to stop.

This is a submission for a motorized scooter, not an AI/ML powered medical device. As such, the requested information regarding AI/ML-specific study design, such as acceptance criteria based on performance metrics (e.g., sensitivity, specificity), ground truth establishment, expert adjudication, MRMC studies, and training/test set details, is not applicable and therefore not present in the provided text.

The document primarily focuses on demonstrating substantial equivalence to a predicate device through non-clinical testing against relevant standards.

Here's a breakdown of the available information based on your request, highlighting where the requested details are not applicable:

1. Table of acceptance criteria and the reported device performance

2. Sample size used for the test set and the data provenance

• Not Applicable: This is a physical device (scooter), not an AI/ML algorithm that processes data. The "test set" would refer to the specific unit(s) of the scooter tested to ensure compliance with standards, and the provenance would be the manufacturing site (Dongguan Prestige Sporting Goods Co., Ltd. in China). The document does not specify the number of units tested.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not Applicable: For a physical device like a scooter, "ground truth" in the context of expert review for AI/ML performance is not relevant. Compliance with standards is typically assessed through engineering tests and measurements, often performed by certified testing laboratories.

4. Adjudication method for the test set

• Not Applicable: As above, adjudication methods like 2+1 or 3+1 are used for expert consensus on data labeling, which is not relevant for testing a physical mobility 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 device is a motorized scooter, not an AI system designed to assist human readers. MRMC studies are not relevant.

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

• Not Applicable: This is a physical device, not an algorithm.

7. The type of ground truth used

• Engineering/Performance Standards: The "ground truth" for this device is its adherence and demonstrable compliance with established international and national engineering standards (e.g., ANSI/RESNA WC. Vol. I Sec. 7, Sec 8 and sec. 21, CISPR 11, IEC 60335-2-29, IEC 60601-1, IEC 61000-4-2, etc.). This involves objective measurements and tests to ensure safety, functionality, and durability.

8. The sample size for the training set

• Not Applicable: This is a manufactured physical product. There is no "training set" in the context of machine learning.

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

• Not Applicable: As above, no training set for this type of device.

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