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The device is intended for medical purposes to provide mobility to persons restricted to a sitting position.

The Wu's Powered Wheelchair, Mambo 30, is an indoor-use electric wheelchair that is battery operated. It has a base with six-wheeled with a seat and armrest. The movement of the wheelchair is controlled by the rider who uses joystick, located at the right-side armrest, to control the direction and speed of the wheelchair. The device is provided with an off-board battery charger. The maximum weight capacity of Mambo 30 is 300 lbs. (136 kg), and its maximum speed is 4 mph (6.4 km/h).

The provided text describes a 510(k) premarket notification for a powered wheelchair, the Wu's Powered Wheelchair, Mambo 30. The document focuses on demonstrating substantial equivalence to a predicate device, the Wu's Powered Wheelchair, Mambo 36, primarily through performance testing against recognized standards.

Here's an analysis of the acceptance criteria and study information, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document implicitly uses international and domestic standards as acceptance criteria for various aspects of the powered wheelchair. The reported device performance is indicated by its compliance with these standards.

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

The document describes performance testing based on ISO and ANSI/RESNA standards for powered wheelchairs. These standards typically involve testing a single device or a small representative sample of the manufactured device to ensure it meets the specified engineering and safety requirements. The document does not specify a numerical sample size beyond implying testing of "the device" (singular) or its components.

The data provenance is from non-clinical tests conducted by the manufacturer, Wu's Tech Co., Ltd., based in Taiwan, R.O.C. The data is prospective in the sense that the device was actively tested against the standards to demonstrate compliance for regulatory submission.

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

This type of submission (510(k) for a powered wheelchair) does not typically involve human expert consensus for "ground truth" in the way a diagnostic AI device would. The "ground truth" here is objective compliance with established engineering and safety standards. The experts involved would be the engineers and technicians conducting the tests in accordance with the specified ISO and ANSI/RESNA standards, as well as the regulatory reviewers at the FDA who assess the submitted test reports. Their qualifications are implicitly that they are competent in performing and interpreting these engineering tests. The document does not specify the number or specific qualifications of these individuals but relies on the adherence to recognized standards.

4. Adjudication method for the test set:

Not applicable in the context of this device and testing. Adjudication methods like 2+1 or 3+1 are used in studies involving human interpretation or subjective assessments, often for diagnostic accuracy, which is not the nature of these engineering performance tests. The "adjudication" is essentially the successful completion and documentation of tests aligned with the specified 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:

No. This is a powered wheelchair, not a diagnostic imaging device utilizing AI. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not relevant or reported.

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

No. This is a physical medical device. "Standalone performance" in the context of an algorithm is not applicable here. The device's performance is inherently tied to its physical interaction with users and the environment, albeit controlled by electronic systems.

7. The type of ground truth used:

The ground truth used is compliance with established international and national performance and safety standards (ISO 7176 series and ANSI/RESNA WC-2 series), and biocompatibility testing standards (ISO 10993-1). This is an objective, measurable ground truth for engineering and material safety.

8. The sample size for the training set:

Not applicable. This device does not involve a "training set" in the context of machine learning or AI. Its design and performance are based on engineering principles and compliance with fixed standards, not on learning from a dataset.

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

Not applicable. See point 8.

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The device is intended for medical purposes to provide mobility to persons restricted to a seated position.

The WU'S Powered Wheelchair MAMBO 36 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.

This is a 510(k) premarket notification for a Powered Wheelchair, which is a Class II medical device. The information provided describes the performance testing and comparison to a predicate device, as opposed to a study on software or AI performance. Therefore, many of the requested categories (such as sample size for test/training sets, expert qualifications, adjudication methods, MRMC studies, and standalone algorithm performance) are not applicable to this type of submission.

Here's an analysis of the provided text in the context of your request:

1. Table of acceptance criteria and reported device performance:

Notes on "Acceptance Criteria" and "Reported Performance":
For a physical device like a powered wheelchair, the "acceptance criteria" are generally established by the referenced standards (e.g., ANSI/RESNA WC/Vol.2-1998 for performance, CISPR 11 for EMC). The document states that the new device passed these tests or met the requirements, which implies it met the acceptance criteria implicitly defined by those standards.

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

• Sample Size: Not applicable. This submission is for a physical device and references performance testing against established standards for a single device, not a data-driven study with a test set.
• Data Provenance: Not applicable. The testing appears to be physical testing of the device itself, likely performed in Taiwan where the manufacturer is located.

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. Ground truth as typically understood in AI/software validation (e.g., expert consensus on medical images) is not relevant for the performance testing of a powered wheelchair. The "ground truth" for a wheelchair's performance is adherence to engineering and safety standards.

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

• Not applicable. No expert adjudication method is mentioned or relevant for this type of device submission.

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 a submission for a physical medical device, not an AI or software assistant designed to improve human reader performance.

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 (expert consensus, pathology, outcomes data, etc):

• Not applicable in the typical sense. The "ground truth" for this device's performance is compliance with established international and national standards for wheelchair safety and performance (e.g., ANSI/RESNA, CISPR, EN, IEC standards). This is determined through physical testing and measurement.

8. The sample size for the training set:

• Not applicable. This is not a machine learning model, so there is no "training set."

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

• Not applicable. There is no training set mentioned.

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The device is intended for medical purposes to provide mobility to persons restricted to a seated position.

The WU'S Powered Wheelchair MAMBO 2 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.

This 510(k) submission (K052559) for the WU'S POWERED WHEELCHAIR, MAMBO 2, is a premarket notification where substantial equivalence to a predicate device is claimed. As such, the concept of "acceptance criteria" and a "study that proves the device meets the acceptance criteria" in the context of performance metrics (like accuracy, sensitivity, specificity, etc.) for AI/imaging devices is not directly applicable here.

Instead, the acceptance criteria are generally related to demonstrating that the new device is as safe and effective as a legally marketed predicate device. This is primarily achieved through comparing technical characteristics, materials, and compliance with recognized standards.

Here's a breakdown of the requested information based on the provided text, adapted to the context of a medical device submission focused on substantial equivalence:

1. Table of Acceptance Criteria and Reported Device Performance

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

This submission does not describe a "test set" in the context of clinical data for performance evaluation as would be seen for an AI/imaging device. The assessment is based on a comparison of device specifications, materials, and compliance with recognized standards, primarily through engineering testing and documentation.

• Sample Size: Not applicable in the conventional sense of a clinical test set. The "samples" are the devices themselves undergoing physical and electrical testing.
• Data Provenance: The information is derived from internal design specifications, material certifications (e.g., UL), and engineering test results (such as EMC Report, ANSI / RESNA WC/Vol.2-1998, CISPR 11, EN61000-3-2, IEC61000-3-3). The manufacturer is WU'S TECH CO., LTD. located in Hsin Chu City, China (Taiwan). The testing is implied to be prospective engineering and material testing rather than retrospective clinical data analysis.

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 a study requiring expert consensus for a "ground truth" on clinical data. The "ground truth" here is the adherence to engineering standards and safety specifications, which is verified through standard testing procedures and certifications (e.g., UL).

4. Adjudication Method for the Test Set

Not applicable. There is no clinical test set requiring adjudication in this submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for evaluating the impact of AI on human reader performance, typically in diagnostic imaging. The Mambo 2 is a powered wheelchair, and its approval process does not involve such studies.

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

Not applicable. This is not an algorithmic device.

7. The Type of Ground Truth Used

The "ground truth" in this context is established by:

• Predicate Device Characteristics: The established safety and effectiveness of the legally marketed predicate device (WU'S POWERED WHEELCHAIR, MAMBO 3, K030707).
• Engineering Standards: Compliance with recognized international and national standards for wheelchairs (e.g., ANSI / RESNA WC/Vol.2-1998, CISPR 11, EN61000-3-2, IEC61000-3-3 for electrical and mechanical safety, strength, fatigue, etc.).
• Material Certifications: Certifications for components like batteries and chargers (e.g., UL certification).
• Control System Clearances: The control systems used are FDA-cleared.

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

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The device is intended for medical purposes to provide mobility to persons restricted to a seated position.

The WU'S Powered Wheelchair MAMBO F120 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 describes the 510(k) summary for the WU'S POWERED WHEELCHAIR, MAMBO F120. This documentation focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific device performance against a set of acceptance criteria for a novel medical AI/ML device. Therefore, much of the requested information regarding AI/ML study design, sample sizes, ground truth establishment, expert adjudication, and MRMC studies is not applicable to this submission.

However, I can extract the relevant performance testing information that was included to support the claim of substantial equivalence.

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

The document does not present acceptance criteria in a quantitative, pass/fail table format with specific thresholds. Instead, it refers to compliance with recognized standards. The "reported device performance" is essentially that the device "passed" these standards.

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 applicable. The performance testing refers to engineering and electrical safety standards for the device itself, not a clinical study involving a test set of data.

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 is not an AI/ML device requiring expert-established ground truth.

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

Not applicable.

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.

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

The device is a physical powered wheelchair, not an algorithm. Therefore, "standalone performance" in the context of an algorithm is not applicable. The performance tests assess the standalone physical and electrical characteristics of the wheelchair.

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

For the physical and electrical safety performance testing, the "ground truth" is defined by the technical specifications and limits set forth in the referenced international and national standards (e.g., CISPR 11, EN61000-3-2, IEC61000-3-3, ANSI / RESNA WC/Vol.2-1998, UL certification). Compliance with these standards is considered the "ground truth" for the device's acceptable performance in these areas.

8. The sample size for the training set

Not applicable. This device does not involve a training set for an AI/ML algorithm.

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

Not applicable.

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The device is intended for medical purposes to provide mobility to persons restricted to a seated position.

The WU'S Powered Wheelchair MAMBO 36X 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 describes a 510(k) premarket notification for a powered wheelchair, the WU's POWERED WHEELCHAIR, MAMBO 36X. This document focuses on establishing substantial equivalence to a legally marketed predicate device, the TEH LIN JUPITER Powered Wheelchair TL-320 (K022697), rather than detailing acceptance criteria and performance data from a specific study designed to "prove the device meets acceptance criteria" in the way one might expect for a novel AI/software-as-a-medical-device (SaMD) product.

Therefore, many of the requested categories (e.g., sample size for test set, number of experts, adjudication method, MRMC studies, ground truth details, training set size) are not applicable or cannot be extracted directly from this type of regulatory submission for a powered wheelchair.

Here's an analysis based on the provided text, addressing the applicable points and explaining why others are not present:

Acceptance Criteria and Study for WU's POWERED WHEELCHAIR, MAMBO 36X

This 510(k) submission primarily focuses on demonstrating substantial equivalence to a predicate device, as opposed to a de novo approval or clinical trial for a novel device. Therefore, the "acceptance criteria" are largely based on meeting established standards and demonstrating similarity in safety and performance to the predicate device. The "study" referenced is the performance testing against these standards, which are not designed to measure metrics like sensitivity, specificity, or accuracy (which are common for AI/SaMD devices).

1. Table of Acceptance Criteria and Reported Device Performance

• EMC Report ANSI / RESNA WC/Vol.2-1998: Standard for electrically powered wheelchairs, scooters, and their chargers - requirements and test methods.
• CISPR 11: 1990: Industrial, scientific and medical (ISM) radio-frequency equipment – Electromagnetic disturbance characteristics – Limits and methods of measurement.
• EN61000-3-2: 1995: Limits for harmonic current emissions.
• IEC61000-3-3: 1995: Limitation of voltage changes, voltage fluctuations and flicker in public low-voltage supply systems.
• Electronic systems are UL certified. |
  | Minor Differences (Not impacting safety) | Differences in overall dimensions, seat size, weight limit, speed, range, incline. | The major differences existing are the overall dimension, the size of seat, weight limit, maximum speed, cruising range, and the incline degrees. The overall appearance differences are "not safety aspect" and do not affect substantial equivalence. |

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

• Sample Size: Not applicable in the context of this 510(k) for a powered wheelchair. Performance testing refers to engineering and electrical safety standards applied to the device itself (e.g., a sample unit of the wheelchair), not a patient-based test set or data set in the manner of AI/SaMD.
• Data Provenance: Not applicable. The "data" here are test results from engineering and electrical safety evaluations of the device's physical and electrical characteristics.

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/SaMD context, refers to a definitively correct label or outcome for a medical condition. For a powered wheelchair, "ground truth" relates to compliance with engineering standards, which is assessed through standardized testing and certification by notified bodies (e.g., UL, and compliance to standards like ANSI/RESNA).

4. Adjudication Method for the Test Set

• Not applicable. This concept is relevant for reconciling discrepancies in expert opinions on medical data, which is not part of this type of device submission.

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 a powered wheelchair, not an AI-powered diagnostic or assistive tool for human readers (e.g., radiologists).

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

• Not applicable. This device does not involve a standalone algorithm.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

• Not applicable in the typical medical imaging/AI sense. The "ground truth" for this device is based on established engineering and electrical safety standards (e.g., ANSI/RESNA, CISPR, EN, IEC) as assessed through physical and electrical performance tests. Successful passing of these tests serves as the "truth" that the device meets the safety and performance requirements.

8. The Sample Size for the Training Set

• Not applicable. This device does not employ machine learning or AI that requires a "training set."

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

• Not applicable, as there is no training set for this device.

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The device is intended for medical purposes to provide mobility to persons restricted to a sitting position.

WU'S POWER WHEELCHAIR, MAMBO 3

This document is a 510(k) premarket notification letter from the FDA for a power wheelchair. It is not a study report and therefore does not contain any information regarding acceptance criteria or the results of a study proving a device meets these criteria.

The letter essentially states that the FDA has reviewed the submission for the "WU'S Power Wheelchair, MAMBO 3" and determined it is "substantially equivalent" to legally marketed predicate devices. This means it can be marketed, subject to general controls provisions.

To directly answer your request:

1. A table of acceptance criteria and the reported device performance: Not available in this document.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not available in this document.
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 available in this document.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not available in this document.
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 available in this document. This device is a power wheelchair, not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not available in this document. This device is a power wheelchair.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not available in this document.
8. The sample size for the training set: Not available in this document.
9. How the ground truth for the training set was established: Not available in this document.

In summary, this document is solely an FDA clearance letter and does not provide the detailed study information you are seeking.

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The device is intended for medical purposes to provide mobility to persons restricted to a sitting position.

WU'S Power Wheelchair, MAMBO 5

This document is a 510(k) clearance letter from the FDA for the WU'S Power Wheelchair, MAMBO 5. It confirms that the device is substantially equivalent to legally marketed predicate devices. However, this type of document does not contain the detailed acceptance criteria or a study proving that the device meets those criteria, as typically found for AI/ML medical devices.

Medical devices like power wheelchairs are regulated differently from AI/ML software. Their "acceptance criteria" primarily relate to performance standards, safety, and functional requirements, which are typically established through engineering tests, usability assessments, and predicate device comparison, rather than clinical studies with ground truth established by experts.

Therefore, most of the requested information regarding AI/ML device studies, ground truth, expert consensus, and sample sizes for training/test sets is not applicable to this document. The document confirms market clearance based on substantial equivalence to a predicate device.

Here's what can be extracted based on the nature of the device and the document provided:

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

• Not explicitly provided in this document. For a power wheelchair, acceptance criteria would typically involve:
  • Safety standards: e.g., electrical safety, mechanical stability, braking effectiveness.
  • Performance standards: e.g., maximum speed, range per charge, weight capacity, obstacle climbing ability, turning radius, durability.
  • Usability: ease of operation, comfort.
• The document states that the device is "substantially equivalent" to legally marketed predicate devices. This implies that the device meets the same performance and safety standards as those predicates. Therefore, the "reported device performance" is essentially congruent with that of existing compliant power wheelchairs.

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

• Not applicable / Not provided. This information is relevant for clinical studies or AI/ML model validation, not for the regulatory clearance of a physical medical device like a power wheelchair. Testing for a wheelchair would involve engineering and performance tests on the device itself, not a "test set" of patient data.

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 / Not provided. "Ground truth" established by experts is a concept for evaluation of diagnostic or AI/ML tools. For a power wheelchair, ground truth is established by physical measurement, engineering standards, and user testing.

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

• Not applicable / Not provided. Adjudication methods are used in clinical trials or expert reviews, not typically for the direct testing of a physical device like a wheelchair.

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 was not done and is not applicable. MRMC studies are specifically for evaluating AI/ML-assisted diagnostic tools where "human readers" (e.g., radiologists, pathologists) interpret data. This device is a power wheelchair.

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

• No, this was not done and is not applicable. This concept pertains to AI/ML software performance. The "algorithm" of a power wheelchair is its mechanical and electrical design, not a diagnostic algorithm.

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

• For a power wheelchair, ground truth would be based on:
  • Engineering standards: e.g., ANSI/RESNA standards for wheelchairs and scooters.
  • Physical measurements and tests: e.g., measuring speed, stability, battery life, weight capacity.
  • Usability assessments: observing users operating the device.
  • Safety compliance: ensuring adherence to electrical, mechanical, and fire safety regulations.
• The document implies that these types of "ground truth" (i.e., compliance with relevant standards and predicate performance) were met implicitly through the substantial equivalence determination.

8. The sample size for the training set

• Not applicable / Not provided. This is irrelevant for a physical mechanical/electrical device.

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

• Not applicable / Not provided. This is irrelevant for a physical mechanical/electrical device.

In summary, this FDA clearance letter for a power wheelchair does not contain the information requested because the device type and regulatory pathway are fundamentally different from those applicable to AI/ML medical devices where such detailed study and ground truth information would be available. The clearance is based on demonstrating "substantial equivalence" to existing, legally marketed predicate devices, meaning it performs as safely and effectively as similar devices already on the market, meeting established safety and performance standards.

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