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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 product consists of frame, wheels, seat, armrest, lithium battery, motor and controller with a lightweight and compact design.The entire wheelchair can be disassembled, making it easy to carry. The wheelchair comes equipped with an electronically controlled rising seat that allows the user 280mm/11" of seat height adjustment using the joystick. The armrest can be flipped upside down, which is convenient for the elderly to move. Users can drive the wheelchair by themselves through the control device. The wheelchair uses lead-acid Battery as its power source. The controls the drive leftright motor to realize the wheelchair forward, backward and turn functions. The frame of the device is carbon steel. The front wheels suitable for rotation, acceleration, retrograde and other actions of the wheels movement will be achieved by thrust generated from the rear wheels are driving wheels to control the speed and direction. The wheels are Solid PU tires. When in use, the operator drives the motor of the rear wheel by operating the controller joystick to achieve the rear wheels movement. The DC brushless motor and brake system are fixed on the rear wheels. The max loading of the device is 136KG. Only for one person sit.

The provided text is a 510(k) summary for an electrically powered wheelchair. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study with specific acceptance criteria and detailed device performance metrics in the format requested.

Therefore, many of the requested elements of information, such as sample sizes, data provenance, expert qualifications, and MRMC study details, are not applicable or not available in this type of document, as it describes the testing and comparison of a physical medical device (a wheelchair) rather than a diagnostic AI algorithm.

However, I can extract the acceptance criteria as indicated by compliance with various ISO standards and the 'reported device performance' based on the comparison table and the general statements about meeting requirements.

Here's the closest representation of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not specify a distinct "test set" in terms of patient data or case numbers. Instead, it refers to performance and safety testing of the physical device according to various international standards (ISO). For tests involving a dummy, it mentions validation "with the maximum rated weight dummy." The number of devices tested is not explicitly stated.
• Data Provenance: The testing appears to have been conducted as part of the device development and verification process by the manufacturer in China. The specific location or date of individual tests are not detailed beyond the document preparation date (2025/2/26). The studies are inherently "prospective" in the sense that they are conducted to verify the new device's compliance.

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

• This section is not applicable. The device is an electrically powered wheelchair, not an AI diagnostic algorithm or system requiring expert-established ground truth from medical images or patient data. The "ground truth" for the device's performance is established by its compliance with engineering and safety standards, which are defined by standard bodies (like ISO) and regulatory bodies (like FDA), and verified through physical testing.

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

• This section is not applicable. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies to resolve discrepancies among multiple expert readers for diagnostic tasks. For a physical device like a wheelchair, performance is measured against objective engineering and safety standards, not subjective expert assessment of 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:

• This section is not applicable. An MRMC study is relevant for evaluating the impact of AI on human reader performance in diagnostic tasks. This document is for a physical medical device (a wheelchair) and does not involve AI for diagnostic purposes or human readers.

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

• This section is not applicable. There is no AI algorithm being evaluated for standalone performance in this document. The device is a physical wheelchair.

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

• The "ground truth" in this context is defined by the technical specifications, requirements, and acceptable tolerances outlined in the referenced international standards (e.g., ISO 7176 series, ISO 10993 series, IEC 60601-1-2) which are based on engineering principles, safety considerations, and recognized testing methodologies. It's essentially engineering and safety standard compliance verified through objective physical testing.

8. The sample size for the training set:

• This information is not applicable as this document does not describe the development or testing of an AI model with a training set.

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

• This information is not applicable as this document does not describe the development or testing of an AI model with a training set.

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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 Electrically powered wheelchair is a motor driven, indoor 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.

It is mainly composed of front wheel, drive wheel, frame, controller (joystick), motor and drive devices, armrest, backrest, seat belt, footrest, battery box and charger.

The device is powered by Li-ion Battery pack (25V 10Ah) with 11.8 Km range, which can be recharged by an off-board battery charger that can be plugged into an AC socket outlet(100-240V, 50/60Hz) when the device is not in use.

The user can activate the controller handle (joystick) to control the speed and direction of the wheelchair movement. When the user releases the joystick will automatically go 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 is a 510(k) summary for an electrically powered wheelchair (HP202). It focuses on demonstrating "substantial equivalence" to a legally marketed predicate device (K230964) rather than proving the device meets specific acceptance criteria through a clinical study of an AI/software component.

Therefore, the request for details related to AI/software performance evaluation (like acceptance criteria for an AI model, sample sizes for test/training sets, expert consensus, MRMC studies, standalone performance, etc.) cannot be fully answered from the provided text.

The document states: "No clinical study is included in this submission." and primarily relies on non-clinical testing against established ISO standards and direct comparison of specifications to the predicate device to argue for substantial equivalence.

Here's an attempt to answer the questions based only on the provided text, highlighting where information is absent for AI-specific criteria:

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

The acceptance criteria are generally implied by conformity to specific ISO standards and the performance metrics of the predicate device. The document presents a comparison table (Table 1: General Comparison, and implicitly Table 3: Performance Comparison) rather than a formal acceptance criteria table with a "Pass/Fail" or "Meets" column. The "Remark" or "Results" columns in these tables serve a similar purpose by indicating "S.E." (Substantially Equivalent) or explaining minor differences that do not raise new safety or effectiveness concerns.

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 as no clinical study was conducted. The testing described is primarily physical device testing against engineering standards. The manufacturer is based in 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)

This information is not provided as no clinical study or expert-based ground truth establishment (relevant for AI/image analysis) was performed.

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

This information is not provided as no clinical study or expert-based ground truth establishment was performed.

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 MRMC study was done. The device is an electrically powered wheelchair, not an AI-assisted diagnostic tool for human readers.

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

A standalone performance test for an AI algorithm was not performed because the device itself is an electrically powered wheelchair and the submission does not describe an AI algorithm component requiring such testing. The "software validation" mentioned relates to the wheelchair's control system, not an AI for interpretation or diagnosis.

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

The "ground truth" for this device's performance is established by conformance to internationally recognized engineering standards (ISO 7176 series, ISO 10993 series) and direct comparison of technical specifications and safety features to a legally marketed predicate device. This is a non-clinical "ground truth."

8. The sample size for the training set

This information is not provided as no AI training set was described or used in this submission.

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

This information is not provided as no AI training set was described or used in this submission.

In summary: The provided FDA 510(k) summary for the "Electrically powered wheelchair (HP202)" demonstrates substantial equivalence through non-clinical testing against ISO standards and direct comparison to a predicate device. It does not involve a clinical study or the evaluation of an artificial intelligence/software component where the requested details about acceptance criteria, sample sizes, expert ground truth, or human-AI interaction would be relevant.

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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 product consists of frame, wheels, seat, armrest, lithium battery, motor and controller with a lightweight and compact design. The whole wheelchair can be folded by one button and it can be easily carried or rolled after folding, The seat cushion is detachable. The armrest can be flipped backward, which is convenient for the wheelchair by the wheelchair by themselves through the control device.

The wheelchair uses lithium batteries as its power source. The drive left/right motor to realize the wheelchair forward, backward and turn functions.

The frame of the device is carbon fiber. The front wheels suitable for rotation, acceleration, retrograde and other actions of the wheelchair. The front wheels mover will be achieved by thrust generated from the rear wheels are driving wheels to control the speed and direction. The wheels are Solid PU tires.

When in use, the operator drives the motor of the rear wheel by operating the controller handle (joystick) to achieve the rear wheels movement.

The DC Brushless motor and Brake system are fixed on the rear wheels. The max loading of the device is 125KG. Only for one person sit.

This is an FDA 510(k) premarket notification for an Electrically Powered Wheelchair (K241632).

For devices like this (powered wheelchairs), the acceptance criteria and study that proves the device meets them typically involve demonstrating substantial equivalence to a legally marketed predicate device, primarily through non-clinical performance testing to relevant international standards. Unlike AI/ML-based medical devices, there isn't a "test set" in the sense of a dataset for algorithm evaluation, nor are there "expert readers" establishing ground truth in the same way. The "performance" refers to the physical and functional aspects of the wheelchair.

Here's a breakdown based on the provided document:

Acceptance Criteria and Reported Device Performance

The document states that the device's acceptance criteria are met by demonstrating compliance with various international ISO and IEC standards relevant to electrically powered wheelchairs. The reported "performance" is inherently tied to passing these standards.

Table 1: Acceptance Criteria and Reported Device Performance

The document explicitly states: "The conclusions drawn from the nonclinical tests demonstrate that the subject device is as safe, as effective, and performs as well as the legally marketed predicate device K231508."

Study Details

Given the nature of the device (electrically powered wheelchair) and the information provided in the 510(k) summary, the "study" is a series of non-clinical, bench-top, and possibly simulated-use tests to demonstrate compliance with the referenced international standards.

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

   • Sample Size: The document does not specify a numerical sample size (e.g., number of wheelchairs tested). For non-clinical performance testing of physical devices, testing typically involves a representative sample or a single unit (depending on the test standard and design).
   • Data Provenance: The document does not explicitly state the country of origin for the testing data itself. The applicant is Kunshan Hi-Fortune Health Products Co., Ltd in China, and their consultant is in Shanghai, China. It is highly probable that the testing was conducted in laboratories in China, often by accredited testing houses. The testing would be considered prospective in the sense that it was conducted specifically to demonstrate compliance for this 510(k) submission.

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

   • This question is not applicable in the context of this device and 510(k) submission. "Ground truth" established by experts (like radiologists for AI algorithms) is not a component of demonstrating substantial equivalence for an electrically powered wheelchair. The "ground truth" here is the pass/fail criteria defined by the requirements of the international standards themselves. Compliance is verified by engineers and technicians performing the tests according to standard protocols.

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

   • This is not applicable. Adjudication methods like 2+1 or 3+1 are used for expert consensus on image interpretation or clinical outcomes, typically in studies involving human readers or clinical trials. For non-clinical performance testing against engineering standards, compliance is objectively measured.

4. 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. MRMC studies are used to evaluate AI-assisted diagnostic devices in a clinical reading setting. This 510(k) is for a powered wheelchair, not a diagnostic device.

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

   • This refers to AI algorithm performance. This is not applicable as this is not an AI/ML device. The "standalone performance" refers to the physical functionality of the wheelchair according to the specified standards.

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

   • The "ground truth" for this device's performance is objective compliance with the pass/fail criteria and specifications outlined in the referenced international standards (e.g., maximum speed, turning radius, battery performance, mechanical strength, electromagnetic compatibility limits, flammability). It is a standards-based performance evaluation, not clinical outcomes or expert interpretation.

7. The sample size for the training set:

   • This is not applicable. There is no "training set" in the context of a physical device like a powered wheelchair unless it uses an AI/ML component (which is not described or implied here). The design and engineering of the wheelchair are based on established principles, not a data training set.

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

   • This is not applicable for the same reasons as above.

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