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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 product is a Mobility Scooter which provides transport for the disabled and the elderly and to be used both indoors and outdoors.

This scooter is a battery powered four wheeled vehicle. It consists two Lead-acid batteries (in the battery box) with an off-board battery charger, frame, a seat, a back support, control panel (including the key switch, throttle control lever, horn button, speed adjustment dial, and the battery condition meter), two foldable handles, two rear drive wheels with motor/ e-magnetic brake components, two front wheels, anti-tip devices, an external battery charger, a control panel and a motor controller. For convenience of transportation and reduction of possible damage, the battery and the seat unit can be dismantled and separately packaged.

The front wheels of the scooter are 8 inches and the rear wheels are 9 inches.
The motor of the scooter is 24VDC,150W,4200RPM; the Lead-acid Battery is 12 V, 22 Ah, 18.7 Ah; the charger is 24V/2A.
Max. loading cannot be over than 180kg.
The maximum distance travelled with a fully charged battery is 17.5km and the maximum forward speed is 1.6m/s(5.8km/h).
Braking time is less than 2 seconds, braking distance is ≤1.0 meters.

This document is an FDA 510(k) Clearance Letter for a Mobility Scooter (MS160C). It is not an AI/ML medical device, and therefore does not contain the information typically associated with studies proving the performance of an AI/ML algorithm.

The request asks for details like "sample size used for the test set," "number of experts used to establish ground truth," "adjudication method," "MRMC comparative effectiveness study," and "standalone performance," which are specific to the evaluation of AI/ML software. This information is irrelevant to a physical device like a mobility scooter.

Therefore, I cannot provide the requested information as it is not present in the provided document. The document focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance and safety testing against established standards (ISO, IEC).

Here's why each point in your request cannot be answered based on the provided text:

1. A table of acceptance criteria and the reported device performance: While the document lists performance characteristics in "Table 2 - Performance Comparison", these are not presented as "acceptance criteria" in the sense of accuracy/sensitivity/specificity targets for an AI algorithm. Instead, they are comparisons to a predicate device and compliance with established ISO standards. I can extract performance characteristics, but not "acceptance criteria" for an AI model.
2. Sample sized used for the test set and the data provenance: Not applicable. This refers to data for an AI model. The mobility scooter underwent physical product testing.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth and expert review are for AI model validation.
4. Adjudication method: Not applicable. Adjudication is for resolving discrepancies in AI model output or expert readings.
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 for evaluating AI's impact on human performance in diagnostic tasks.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This device is a physical product, not an algorithm.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable. "Ground truth" is a concept for AI model training and validation.
8. The sample size for the training set: Not applicable. This refers to data for an AI model.
9. How the ground truth for the training set was established: Not applicable. This refers to data for an AI model.

However, I can extract information related to the device's performance testing based on the provided document:

Study that proves the device meets requirements (Non-Clinical Testing):

The study was a series of non-clinical tests conducted to verify that the proposed device (Mobility Scooter MS160C) met all design specifications and was substantially equivalent (SE) to the predicate device (Mobility Scooter Model: W3468, K220207).

1. Table of Acceptance Criteria (as reported performance against standards, not AI-specific criteria) and the Reported Device Performance:

The document describes compliance with various ISO and IEC standards as the basis for demonstrating safety and effectiveness. The "acceptance criteria" are implied by adherence to these standards, and the "reported performance" is demonstrated by the test results confirming this compliance.

Key Performance Characteristics (from Table 2 - Performance Comparison):

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

• Sample Size: The document does not specify the number of units tested. For physical device performance testing against standards, it's common to test a representative number of units, but this specific number is not provided in the summary.
• Data Provenance: The tests are non-clinical, meaning they were conducted in a laboratory or controlled setting, presumably as part of the manufacturer's (Suzhou Master Machinery Manufacturing Co., Ltd., China) quality assurance and regulatory submission process. There is no mention of data from human subjects or specific geographical origin for "data provenance" in the sense of patient data.

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

• Not applicable as this is a physical device, not an AI/ML algorithm requiring expert ground truth for diagnostic or similar tasks. The "ground truth" for the device's performance is established by objective measurements against international standards.

4. Adjudication method:

• Not applicable for a physical medical 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:

• No. This type of study is specific to AI/ML devices interacting with human interpreters.

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

• Not applicable. This is a physical mobility scooter, not an algorithm.

7. The type of ground truth used:

• The "ground truth" for the mobility scooter's performance is established by objective measurements and conformance to international performance, safety, and quality standards (e.g., ISO 7176 series, IEC 60601-1-2, ISO 10993 series). This is not an "expert consensus" or "pathology" in the AI/ML context.

8. The sample size for the training set:

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

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

• Not applicable.

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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 subject device, Model MS160A scooter is mainly battery-powered and driven by a DC motor, with the speed adjusted by a user-controlled panel.

The motor is driven, and the speed is adjusted by a user-controlled panel and speed knob.

The scooter consists of two folding armrests, a seat cushion, a folding frame, two front wheels, two rear drive wheels with a motor/electromagnetic brake assembly, a rechargeable lithium-ion battery, an off-board battery charger, a control panel, and a motor controller.

The MS160A scooter is designed to provide mobility for people limited to those who walk unchanged or for the elderly.

Folding design: Pull out the seat and backrest fixing pins, push the backrest forward, the seat and backrest fold into each other, release the handlebar locking knob, push the handlebar backward, the handlebar folds down, the whole scooter is folded.

Control panel: Includes speed knob, battery gauge, power key switch, horn button, throttle control lever, headlight switch, charger port, fuse.

Wheel and frame connection method: the motor is connected to the differential, the differential is connected to the frame, the wheels are mounted on both ends of the differential, the motor rotates with the differential, thus driving the scooter.

Frame design:

1. The frame of MS160A is aluminum alloy.
2. The folding mechanism is operated in two ways:
   a. In the non-riding state, pull out the seat fixing pin, push the backrest forward, the seat and backrest can be folded.
   b. Loosen the handlebar locking knob, push the handlebar forward, the handlebar will fold down.

The front wheels of the scooter are 7 inches and the rear wheels are 10 inches.

The motor of the scooter is ST-62D24-120W; the lithium-ion battery is 25.55V 10.4AH; the charger is 24V/2A.

Max. loading cannot be over than 125kg.

The maximum distance travelled with a fully charged battery is 8.2km and the maximum forward speed is 1.8m/s.

Braking time is about 2 seconds, braking distance is ≤1.5 meters.

The provided document (K242982 510(k) Summary for the Mobility Scooter (MS160A)) is a premarket notification to the FDA for a Mobility Scooter. This type of device is a physical product and not typically associated with AI/ML software or studies involving ground truth establishment by experts, multi-reader multi-case (MRMC) comparative effectiveness studies, or standalone algorithm performance.

Therefore, this document does not contain the information requested regarding acceptance criteria and study proving device meets acceptance criteria related to AI/ML product performance. The studies mentioned primarily confirm the device's compliance with physical safety and performance standards (e.g., ISO 7176 series for wheelchairs, biocompatibility).

Here's why the requested information cannot be extracted from this document:

• Device Type: A mobility scooter is a mechanical device, not imaging or diagnostic software that would rely on AI/ML algorithms to generate results requiring expert consensus or ground truth establishment.
• Study Types: The "non-clinical testing" section details adherence to established ISO standards for physical characteristics like stability, braking, dimensions, and biocompatibility. There is explicitly "No clinical study implemented for the scooter."
• Acceptance Criteria: The "acceptance criteria" for this device are its ability to meet the performance specifications outlined in the ISO standards, and to be "substantially equivalent" to a predicate device based on physical and functional comparisons. These are not acceptance criteria for AI model performance metrics like sensitivity, specificity, or AUC, which would be relevant for devices that interpret data or images.
• Ground Truth, Experts, Sample Sizes (for AI/ML): These concepts are entirely absent because they are not applicable to the type of device being submitted.

In summary, the provided document is for a physical medical device (mobility scooter) and does not involve AI/ML components or related performance studies that would utilize the concepts of ground truth, expert review, or statistical metrics like sensitivity/specificity for algorithm output.

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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.

This Electric Wheelchairs, modes!: MP201C, is a motor driven, indoor and outdoor transportation vehicle, which a device for assisting action handicapped people and disabled people to move. It is suitable for disabled people with mobility difficulties and elderly people.

The device consists of front wheel, drive wheel, frame, controller, motor, armrest, backrest, seat cushion, seatbelt, pedal, battery box and charger.

The device is powered by Li-ion Battery pack with 24 Km range, which can be recharged by an offboard battery charger that can be plugged into an AC socket outlet (100-240V. 50/60Hz) when the device is not in use.

The patient can activate the controller handle (joystick) to control the speed and direction of the wheelchair movement. In addition, when the patient releases the joystick, the joystick will return back to the central position and the wheelchair will be automatically stopped soon due to automatic electromagnetic brake system. Once the joystick is activated again move to other position, the wheelchair will be re-energized.

This document details the 510(k) premarket notification for an Electric Wheelchair (models MP201C, MP201L), asserting its substantial equivalence to a predicate device (K220747). The acceptance criteria and the study proving the device meets these criteria are primarily based on non-clinical testing against a series of ISO 7176, ISO 10993, and IEC 60601 standards.

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

The acceptance criteria are established by the adherence to various international standards for wheelchairs and medical devices. The reported device performance is indicated by the statement that the test results "meet its design specification" or "comply with the following standards."

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

The document does not explicitly state the sample size for non-clinical tests. It refers to various ISO and IEC standards, implying that the test samples and methods prescribed by these standards were followed. The provenance of the data is not specified in terms of country of origin but is implicitly derived from tests conducted by the manufacturer, Suzhou Master Machinery Manufacturing Co., Ltd. (China). The tests outlined are non-clinical, likely prospective in nature as they involve testing the physical device against performance standards.

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 information is not provided. The ground truth for performance is established by the defined parameters and methodologies within the cited ISO and IEC standards, which are internationally recognized. The compliance of the device with these standards is verified through testing.

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

This information is not applicable to non-clinical device performance testing against established standards. The tests are designed to objectively measure specific parameters.

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

No such study was conducted, as this is a physical medical device (electric wheelchair) and not an AI-assisted diagnostic or interpretative tool that would involve human readers.

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

This question is not applicable. The device is an electric wheelchair, not an algorithm.

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

The ground truth for the non-clinical tests is based on pre-defined specifications and international performance standards (ISO, IEC). These standards establish objective metrics and test methods for evaluating the safety and effectiveness of wheelchairs. For example, for "Braking distance $\leq$ 1.5 m," the ground truth is the specified maximum allowed distance according to relevant standards.

8. The sample size for the training set

This is not applicable as this is a physical medical device, not a machine learning or AI model that requires a training set.

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

This is not applicable, as there is no training set for this 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.

The subject device, Model HS186B Mobility Scooter, 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 a base with frame, two front wheels, two rear wheels, two anti-tip wheels, a seat, a tiller, a control panel, an electric motor, an electromagnetic brake, a rechargeable Lithium-lon Battery with a charger. The movement of the scooter is controlled by the rider who operates the throttle Control Lever, speed knob and hand grips. 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. The Scooter is suitable for use indoors and on flat roads near buildings.

The provided text is a 510(k) summary for a medical device (HS186B Scooter) and an FDA clearance letter. It details a comparison between the proposed device and a predicate device, focusing on non-clinical testing and safety features to demonstrate substantial equivalence. However, it does not describe acceptance criteria for an AI device or a study involving AI performance metrics.

Therefore, I cannot fulfill your request for:

• A table of acceptance criteria and reported device performance for an AI device.
• Sample size used for the test set and data provenance for an AI device.
• Number of experts and their qualifications for establishing ground truth for an AI test set.
• Adjudication method for an AI test set.
• MRMC comparative effectiveness study results (AI improvement vs. without AI assistance).
• Standalone AI performance.
• Type of ground truth used for AI.
• Sample size for AI training set.
• How ground truth for AI training set was established.

This document pertains to a physical medical device (a motorized scooter) and its performance is evaluated against ISO standards and through comparison with a predicate device, not through AI-specific metrics. The "Non-Clinical Testing" section describes adherence to various ISO standards relevant to wheelchairs and scooters, and a "Biocompatibility" assessment. The document explicitly states "No clinical study implemented for the scooter." It does not mention any AI components or related studies.

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