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As a motorized portable electric vehicle for indoor or outside use by persons with medical conditions requiring assistance.

A battery operated lightweight portable mobility device designed for personal travel indoors and limited outdoor use and available in 4 wheel configurations. It is used in a sitting position and operated by a hand controlled throttle located on the handle bars. Braking is automatically controlled when releasing the throttle by the electronic controller and magnetic motor brake. The product is supplied ready to use with a battery and charger and it can be disassembled and folded for transport. Steel frame, battery cycle life of Sealed Lead Acid battery is 400 charging times, 24V15ah Lithium battery is 1000 charging times, 24V12ah Lithium battery is 800 charging times.

The provided document is a 510(k) summary for the "SupaScoota" Motorized Vehicle, Spartan (Sumo) / Spartan SP (Sumo SP). It details the device's characteristics and its substantial equivalence to a predicate device, rather than a clinical study evaluating the device's performance against specific acceptance criteria for AI-related software. Therefore, much of the requested information regarding AI-specific acceptance criteria and study details cannot be extracted from this document.

However, I can provide information based on the listed non-clinical testing performed to establish safety and effectiveness for this type of medical device (a motorized vehicle).

Here's a breakdown of what can be extracted and what cannot:

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

The document does not explicitly state "acceptance criteria" in a table format with corresponding "reported device performance" for each criterion. However, it lists several ISO 7176 standards that the device underwent testing for. The general acceptance criterion implied is compliance with these standards. The document states: "All test results are in compliance with it and were similar to predicate device."

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

This information is not provided in a 510(k) summary for a physical device. Non-clinical testing typically involves specific test samples of the device and its components. "Data provenance" as typically understood in AI studies (e.g., country of origin of data, retrospective/prospective) is not applicable here as these are performance tests of the device itself.

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 is not applicable. The "ground truth" for the non-clinical tests of a motorized vehicle are established by the international standards (ISO) themselves through defined testing methodologies and equipment, not by human experts evaluating outputs.

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

This is not applicable, as there is no expert adjudication for the performance of a physical device against engineering 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 is not applicable. This document describes a physical motorized medical device, not an AI or software device that assists human readers.

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

This is not applicable. This document is about a physical medical device.

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

The "ground truth" for the non-clinical tests of this motorized vehicle is defined by the technical specifications and performance requirements outlined in the referenced ISO and IEC standards. For example, for "Static stability test" (ISO 7176-1), the ground truth is simply whether the device remains stable under defined static conditions.

8. The sample size for the training set

This is 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

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

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

The device is a power wheelchair.
Common Name: Powered Wheelchair
Trade Name: "SupaChair" Powered Wheelchair
Classification Name: Powered Wheelchair
Regulation Number: 890.3860
Product Code: ITI
Device Class: Class 2
Model: COMBI 18/ COMBI 20/ COMBI 18SP/ COMBI 20SP

The provided text is a 510(k) premarket notification for a powered wheelchair, the "SupaChair." It outlines the device's technical specifications, intended use, and a comparison to a predicate device to establish substantial equivalence. However, this document does not describe acceptance criteria, a study that proves the device meets those criteria, or the detailed aspects of a clinical study for an AI/ML powered device.

The information provided relates to a physical medical device (a powered wheelchair), not an AI/ML algorithm. Therefore, many of the requested elements (like "multi reader multi case (MRMC) comparative effectiveness study," "standalone (i.e. algorithm only without human-in-the-loop) performance," "ground truth establishment," "training set sample size," etc.) are not applicable to the content of this document.

The document focuses on demonstrating substantial equivalence to an existing predicate device based on technical characteristics and non-clinical testing (ISO standards for powered wheelchairs), rather than performance metrics of an AI/ML algorithm against a defined ground truth.

Therefore, I cannot extract the requested information from the provided text as it is not present. The document focuses on mechanical, electrical, and physical performance of a wheelchair, not the analytical or clinical performance of a diagnostic AI.

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

The device is a powered wheelchair intended to provide mobility to persons restricted to a sitting position. It is available in three models: SAFARI, SAFARI SPORT, and MINI. It is battery operated and has brake systems.

The provided text describes the "SupaChair" Powered Wheelchair and its substantial equivalence to a predicate device for FDA 510(k) clearance. Here's a breakdown of the acceptance criteria and the study information, focusing on the available details:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally based on compliance with ISO 7176 series standards. The document states that "All test results are in compliance with it and were similar to predicate device." However, specific numerical acceptance criteria (e.g., minimum stability angle, maximum braking distance) and the exact performance values for the "SupaChair" are not explicitly detailed in the provided text. The table below summarizes the types of tests conducted and infers that compliance to the respective standard constitutes the acceptance criteria.

2. Sample Size Used for the Test Set and Data Provenance

The document does not explicitly state the sample size of devices used for testing. However, the tests are "non-clinical testing" and refer to "series test" performed on the "SupaChair" powered wheelchair. This suggests that the tests were conducted on physical units of the device.

The data provenance is from Taiwan (R.O.C.), as the applicant is "EUROGREEN INTERNATIONAL INC." located in Changhua County, Taiwan. The tests are prospective in nature, as they are performed to confirm the device's safety and effectiveness before clearance.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided in the document. For non-clinical device testing like this, "ground truth" is typically established by comparing performance against objective international standards (like ISO 7176) rather than expert consensus on a dataset. The "experts" would be the engineers and technicians conducting and verifying the tests in accordance with these standards.

4. Adjudication Method for the Test Set

This information is not applicable/provided. Adjudication methods (like 2+1, 3+1) are typically used in clinical studies involving interpretation of medical images or data by human readers. The tests described are non-clinical, objective performance tests against engineering standards.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is relevant for AI/radiological diagnosis devices. The "SupaChair" is a physical medical device (powered wheelchair), and its performance is evaluated through engineering and safety standards, not through human reader interpretation of data or images.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

N/A. This question is primarily applicable to AI/software-as-a-medical-device. The "SupaChair" is a physical powered wheelchair. The performance referred to is the physical device's performance against established safety and engineering standards.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical testing of the SupaChair is based on compliance with international engineering and safety standards, specifically the ISO 7176 series and IEC 62133. This is an objective, standardized metric rather than expert consensus, pathology, or outcomes data in the traditional sense. The phrase "All test results are in compliance with it" indicates that the established ground truth for safety and effectiveness is meeting these specified standard requirements.

8. The Sample Size for the Training Set

N/A. This concept of a "training set" is relevant for machine learning or AI models. The "SupaChair" is a physical medical device, and its development and testing do not involve AI training sets.

9. How the Ground Truth for the Training Set Was Established

N/A. As mentioned above, there is no "training set" for this type of device.

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As a motorized portable electric vehicle for indoor or outside use by persons with medical conditions requiring assistance.

Motorized portable electric vehicle for indoor or outside use by persons with medical conditions requiring assistance. It is available in multiple models with varying specifications for wheels, size, weight capacity, speed, and travel distance. It uses dynamic braking and electromagnetic brake systems and is powered by SLA or Lithium batteries with an off-board charger.

The provided text describes a submission for a 510(k) premarket notification for a motorized vehicle called "SupaScoota." This document focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria and a study design for a novel medical device AI/ML algorithm.

Therefore, many of the requested elements for describing acceptance criteria and the study that proves the device meets them (especially those related to AI/ML performance, ground truth, expert adjudication, and comparative effectiveness studies) are not applicable to this document. The document describes a traditional medical device submission for a physical product (a motorized vehicle).

However, I can extract information related to the device's performance and the testing conducted to ensure its safety and effectiveness based on the provided text.

Here's a breakdown of the relevant information:

Device: "SupaScoota" Motorized Vehicle

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

The document does not explicitly state "acceptance criteria" in a quantitative, measurable way for each performance metric in the same manner one might expect for an AI/ML algorithm. Instead, it relies on a comparison to predicate devices and compliance with international standards (ISO 7176 series). The performance metrics listed are descriptive specifications of the device.

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

The document does not specify a "test set" in the context of an AI/ML algorithm or a clinical trial with human subjects. The testing described is non-clinical, primarily focusing on engineering and performance standards for the physical device. Therefore, the concept of sample size for a test set and data provenance (country of origin, retrospective/prospective) is not directly applicable in this context. The tests are conducted on the device models themselves.

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 adjudication are concepts typically associated with AI/ML algorithms, especially for diagnostic or prognostic tasks. For this physical device, "ground truth" is established by direct physical measurements, engineering principles, and adherence to international performance standards (ISO 7176 series).

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

Not applicable, as there's no diagnostic or interpretative task by human experts being evaluated.

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.

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

Not applicable. This is not an AI/ML algorithm. The "standalone" performance refers to the device's physical capabilities as tested against ISO standards.

7. The type of ground truth used

For the safety and effectiveness testing of the "SupaScoota" Motorized Vehicle, the "ground truth" is established by:

• International Standards: Compliance with the ISO 7176 series standards (e.g., static stability, dynamic stability, brake efficiency, theoretical distance range, maximum speed, climbing angle, EMC). These standards define measurable performance requirements.
• Engineering Specifications and Measurements: Direct physical measurements and tests of the device's technical characteristics (e.g., wheel size, weight, dimensions, motor output, battery capacity).
• Comparison to Predicate Devices: The key argument for substantial equivalence relies on comparing the "SupaScoota"'s characteristics and performance to legally marketed predicate devices.

8. The sample size for the training set

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

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

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

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