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The Powered wheelchair (mobility robot) is a motor driven transportation vehicle with the intended use to provide mobility to a disabled or elderly person limited to a seated position.

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I'm sorry, but based on the provided FDA 510(k) Clearance Letter, there is no information available regarding acceptance criteria related to device performance or a study that proves the device meets such criteria.

The letter primarily covers:

• The FDA's decision of substantial equivalence for the "Powered wheelchair (mobility robot) (M4, M4U)" to predicate devices.
• Regulatory information such as regulation numbers, product codes, and class.
• General controls and additional regulations applicable to medical devices (e.g., Quality System regulation, UDI rule, MDR).
• Contact information for FDA resources.
• The device's Indications for Use.

The document does not contain details about:

1. A table of acceptance criteria and reported device performance.
2. Sample sizes or data provenance for a test set.
3. The number or qualifications of experts used for ground truth.
4. Adjudication methods.
5. Multi-reader multi-case (MRMC) comparative effectiveness studies.
6. Stand-alone algorithm performance.
7. The type of ground truth used (e.g., pathology, outcomes data).
8. Training set sample sizes.
9. How ground truth for the training set was established.

This type of information, particularly regarding performance studies and acceptance criteria, is typically found in the 510(k) summary document or the full 510(k) submission, which are more detailed technical documents submitted by the manufacturer to the FDA. The clearance letter itself is a notice of the FDA's decision, not a detailed report of the studies performed.

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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.

Ask a specific question about this device

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 and it can be easily carried or rolled after folding. The seat cushion is detachable. 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 lithium batteries as its power source. The controls the drive left/right motor to realize the wheelchair forward, backward and turn functions. The frame of the device is Magnesium alloy. The front wheels are driven wheels suitable for rotation, acceleration, retrograde and other actions of the wheelchair. The front 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 120KG. Only for one person sit.

The provided text is a 510(k) summary for an Electrically Powered Wheelchair (device name: HP558) and does not contain information about acceptance criteria or a study proving device performance in the context of AI/ML or diagnostic applications.

The document discusses the substantial equivalence of the proposed device to a predicate device (HP458E) by comparing their design, functionality, materials, and compliance with various ISO and IEC standards relevant to wheelchairs. It also mentions performance data to verify that the subject device meets design specifications, but this is in the context of standard engineering and safety testing for a medical device (electrically powered wheelchair), not a study assessing AI/ML model performance.

Therefore, I cannot provide the requested information, such as:

1. A table of acceptance criteria and reported device performance: This document lists various technical specifications and safety standards for the wheelchair itself, not performance metrics of an AI algorithm.
2. Sample size, data provenance, number of experts, adjudication method for the test set: These are relevant to studies evaluating AI/ML models on a dataset, which is not what this document describes.
3. MRMC comparative effectiveness study: No such study is mentioned.
4. Standalone performance (algorithm only): The device is a physical wheelchair, not an algorithm.
5. Type of ground truth used: This concept is not applicable to the evaluation described.
6. Sample size for the training set: Not applicable.
7. How ground truth for the training set was established: Not applicable.

The document is a regulatory submission for a physical medical device (an electrically powered wheelchair) and focuses on ensuring its physical safety, effectiveness, and substantial equivalence to an existing device through engineering and biocompatibility testing against established standards. It does not involve AI or diagnostic imaging.

Ask a specific question about this device

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 and it can be easily carried or rolled after folding. The seat cushion is detachable. 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 lithium batteries 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 aluminum alloy. The front wheels suitable for rotation, acceleration, retrograde and other actions of the wheelchair. The front 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 120KG. Only for one person sit.

The provided document is a 510(k) Premarket Notification for an Electrically Powered Wheelchair (HP206). It primarily details the device's characteristics and compares it to a predicate device (HP358EA) to demonstrate substantial equivalence.

However, the document does not contain information about a study proving device performance against specific acceptance criteria, especially not in the context of an AI/human reader study as typically associated with the comprehensive questions asked. The device in question is an Electrically Powered Wheelchair, not a medical imaging or diagnostic AI device that would involve expert readers, ground truth establishment for a test set, multi-reader multi-case studies, or AI algorithm performance metrics like sensitivity, specificity, etc.

The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the device's compliance with established performance standards and safety requirements for electrically powered wheelchairs.

Therefore, I cannot populate the requested table or answer most of the specific questions about AI performance, expert adjudication, or MRMC studies for this device, as these concepts are not applicable to the information provided in the 510(k) submission for a powered wheelchair.

I can, however, extract the performance data and compliance standards mentioned:

1. Table of acceptance criteria and the reported device performance

The document frames "acceptance criteria" as compliance with various ISO standards and FDA guidance. "Reported device performance" is demonstrated through testing against these standards. There isn't a specific quantitative "acceptance criteria" table with corresponding numerical "reported performance" easily extractable for each parameter the way one would for an AI diagnostic device. Instead, the document states that the device "met all design specifications" and provided "support of the substantial equivalence determination" by undergoing the listed tests.

Here's an attempt to structure it based on the available information, understanding that "acceptance criteria" is implied by compliance with the standards, and "reported performance" is that it passed the tests:

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

• Sample Size: Not explicitly stated as a "sample size" in the conventional sense for a clinical trial or algorithm test set with individual cases. The testing refers to the device prototype(s) themselves. For mechanical and electrical performance tests, a limited number of test units (often 1-3) are typically used per test type, depending on the standard. For biocompatibility, material samples are tested.
• Data Provenance: The tests are performed to demonstrate compliance with international standards (ISO, IEC) generally by test labs. The document does not specify geographical provenance for the testing data in terms of "country of origin of the data" being retrospective or prospective from patient cohorts. It's device performance data.

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

• This is not applicable to an electrically powered wheelchair device. "Ground truth" in this context would refer to the physical and electrical safety and performance parameters measured against established engineering and medical device standards. No "experts" are establishing "ground truth" in the diagnostic sense. Compliance is verified by testing according to published, objective standards.

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

• Not applicable. This refers to consensus reading for diagnostic purposes, which is not relevant here.

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 diagnostic device.

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

• Not applicable. This is not an AI algorithm.

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

• The "ground truth" for this device is based on established international performance and safety standards (ISO and IEC, as listed in the document) and FDA guidance for electrically powered wheelchairs. Compliance is demonstrated through physical, electrical, and materials testing.

8. The sample size for the training set:

• Not applicable. This is not an AI device trained on data.

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

• Not applicable.

Ask a specific question about this device

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 subject device, Powered Wheelchair, mainly powered by battery, motivated by DC motor, driven by user controlling joystick and adjusting speed. The Powered Wheelchairs consist of two foldable armrests, a backrest, a seat cushion, a safety belt, a foldable frame, two rear driving wheels with hub motor/electromagnetic brake assemblies, two pivoting casters, two Li-ion batteries, an off-board battery charger, a control panel, and an electric motor controller. The NXN20-209 Powered Wheelchair is intended to provide mobility to a disabled or elderly person limited to a seated position. The Powered Wheelchair has 7 inch front wheel and 12 inch rear tire. The motor of electric wheelchair is DC24V 200W; the battery is 24V 12AH, Li-ion battery; the charger is 24V/3A. Max. loading can not be over than 110Kgs. Max. distance of travel on the fully charged battery is 16.5 km and Max. speed forward is 6km/h. The braking time is about 2s, and the braking distance is less than or equal to 1.76m.

The provided text describes a 510(k) submission for a Powered Wheelchair (NXN20-209). This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than proving clinical effectiveness through a comparative study with a "human-in-the-loop" component as is common for AI/ML-driven diagnostics. The information provided is primarily related to engineering performance and safety standards for the physical device itself.

Therefore, the requested information regarding acceptance criteria and a study that proves the device meets the acceptance criteria, as phrased for AI/ML device performance (e.g., sample size for test set/training set, number of experts, adjudication methods, MRMC studies, standalone performance, ground truth establishment), is not applicable in the context of this traditional medical device submission.

The document states: "No clinical study implemented for the electric wheelchair." This confirms that the typical clinical performance studies asked for in your prompt were not conducted or required for this device's clearance.

Instead of AI/ML-specific performance criteria, the acceptance criteria for this powered wheelchair are based on adherence to recognized international standards for wheelchairs and a comparison of its physical and performance characteristics to a predicate device.

Here's a breakdown of what the document does provide in relation to acceptance criteria and performance:

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

The document includes two comparison tables (Table 1: General Comparison and Table 2: Performance Comparison) that demonstrate the similarity and conformance of the proposed device to a predicate device and relevant standards. While not "acceptance criteria" in the sense of a specific numerical threshold for a diagnostic outcome, these aspects represent the performance benchmarks the device successfully met.

Table 1 & 2 (summarized and adapted to your request format):

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. No human subjects "test set" was used for performance evaluation in the context of an AI/ML algorithm. The testing was non-clinical (bench and engineering tests) based on international standards for mechanical and electrical safety and performance of wheelchairs. The document does not specify a "sample size" for these non-clinical tests in the way one would for a clinical study. Data provenance is implied by the testing standards and the manufacturer's location (China), but not detailed as typical for clinical 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. Ground truth, in the AI/ML sense, is not established for this type of device. Performance is determined through objective, standardized engineering tests.

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

• Not Applicable. Not a clinical study requiring adjudication.

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 diagnostic or image analysis device, so MRMC studies are irrelevant.

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

• Not Applicable. This is a physical powered wheelchair, not an AI algorithm. Software verification and validation (standalone) was done for the device's control software, ensuring it functions correctly, but this is distinct from AI/ML performance.

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

• Not Applicable/Objective Standards. The "ground truth" for this device's performance is compliance with established international engineering and safety standards (e.g., ISO 7176 series, IEC 60601-1-2) which define objective, measurable criteria for stability, speed, braking, etc.

8. The sample size for the training set:

• Not Applicable. No AI/ML training set is mentioned or relevant for this device.

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

• Not Applicable. No AI/ML training set is mentioned or relevant for this device.

In summary: The provided document is for a traditional powered medical device, not an AI/ML-driven diagnostic or imaging device. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to documented compliance with relevant recognized industry standards (primarily ISO and IEC) through non-clinical testing, and demonstrated substantial equivalence to a predicate 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 subject device, Powered Wheelchair, mainly powered by battery, motivated by DC motor, driven by user controlling joystick and adjusting speed. The Powered Wheelchairs consist of two foldable armrests, a backrest, a seat cushion, a safety belt, a foldable frame, two rear driving wheels with hub motor/electromagnetic brake assemblies, two pivoting casters, two Li-ion batteries, an off-board battery charger, a control panel, and an electric motor controller.

The NXN20-208 and NXN20-211 Powered Wheelchair is intended to provide mobility to a disabled or elderly person limited to a seated position.

The Powered Wheelchair has 7 inch front wheel and 11 inch rear tire.

The motor of electric wheelchair is DC24V 200W; the battery is 24V 12AH, Li-ion battery; the charger is 24V/3A.

Max. loading can not be over than 110Kgs.

Max. distance of travel on the fully charged battery is 16 km and Max. speed forward is 6km/h.

The braking time is about 2s, and the braking distance is

The provided document is a 510(k) premarket notification for a Powered Wheelchair (models NXN20-208, NXN20-211). It focuses on demonstrating substantial equivalence to a predicate device (A08 Power Wheelchair, K163204) rather than presenting a study to prove acceptance criteria for a novel device. Therefore, much of the requested information regarding clinical studies, ground truth establishment, expert adjudication, and AI performance is not applicable to this submission.

However, the document does contain "acceptance criteria" through a demonstration of compliance with recognized standards and a comparison of performance characteristics to a predicate device, which serves as a benchmark for safety and effectiveness in this regulatory context.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria (Standard Compliance) and Reported Device Performance

For a medical device like a powered wheelchair, acceptance criteria are generally defined by compliance with a set of established performance standards. The "reported device performance" is demonstrated by the completion of non-clinical tests verifying compliance with these standards.

Performance Characteristics (Comparison with Predicate 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 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.

Ask a specific question about this device

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.

Ask a specific question about this device

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 subject device, Powered Wheelchair, mainly powered by battery, motivated by DC motor, driven by user controlling joystick and adjusting speed. The Powered Wheelchairs consist of two foldable armrests, a backrest, a seat cushion, a safety belt, a foldable frame, two rear driving wheels with hub motor/electromagnetic brake assemblies, two pivoting casters, two Li-ion batteries, an off-board battery charger, a control panel, and an electric motor controller. The NXN20-205 and NXN20-205M Powered Wheelchair is intended to provide mobility to a disabled or elderly person limited to a seated position. The Powered Wheelchair has 7 inch front wheel and 12 inch rear tire. The motor of electric wheelchair is DC24V 200W; the battery is 24V 12AH, Li-ion battery; the charger is 24V/3A. Max. loading can not be over than 110Kgs. Max. distance of travel on the fully charged battery is 16km and Max. speed forward is 5.5km/h. The braking time is about 2s, and the braking distance is ≤790m.

The provided text is a 510(k) Summary for a Powered Wheelchair (NXN20-205, NXN20-205M) and does not contain details about acceptance criteria and a study proving a device meets them in the context of an AI/ML medical device.

The document describes a traditional medical device (a powered wheelchair) and its substantial equivalence to a predicate device based on non-clinical testing against established ISO standards for wheelchairs. There is no mention of AI or machine learning in this report.

Therefore, I cannot provide the requested information, such as:

• Table of acceptance criteria and reported device performance for an AI/ML device: This document details performance specifications for a physical wheelchair (e.g., speed, range, loading capacity, stability), not AI/ML metrics.
• Sample size used for the test set and data provenance: No test set or data provenance for an AI/ML model is mentioned.
• Number of experts used to establish ground truth and qualifications: This is irrelevant for a physical powered wheelchair.
• Adjudication method: Not applicable.
• MRMC comparative effectiveness study: Not conducted as no AI assistance is involved.
• Standalone (algorithm only) performance: Not applicable.
• Type of ground truth used: Not applicable in the context of an AI/ML device.
• Sample size for the training set: No training set is mentioned.
• How the ground truth for the training set was established: Not applicable.

The document indicates that "Software Verification and Validation Testing" was performed in accordance with FDA Guidance for device software functions, but this refers to traditional software engineering validation, not AI/ML model validation with ground truth and performance metrics.

In summary, the provided text does not contain the information required to answer the prompt about acceptance criteria and studies for an AI/ML device.

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The device is a motor-driven, and indoor transportation vehicle with the intended use to provide mobility to a disabled or an elderly person limited to a seated position.

The TUNG KENG Electrically Powered Wheelchair, Joy Rider, is suitable for indoor uses. It is characterized by high portability in comfortable travel, small storage and convenient delivery in daily life. As folding of Joy Rider only takes just a few seconds, so this model increases opportunities for travel and provides small storage. To use Joy Rider makes your travel in any place and at any moment! It is an individual transportation vehicle for disabled and elderly people that experience difficulties in walking. The Joy Rider comes as preassembled, designed to be lightweight, easily maneuvered, highly portable, and most importantly, safe and comfortable.

It is driven by two brushless DC motors, and contains two foldable armrests, a seat belt, a backrest, a seat cushion and small with light texture, a foldable frame, two rear driving wheels with hub motor/electromagnetic brake assemblies, two pivoting casters, one Lithium-ion battery, an off-board battery charger, a control panel, and an electrical controller.

The device is powered by one 24 VDC/ 10.5 Ah Lithium-ion battery with 9.3 miles cruising range that can be recharged by an off-board battery charger, rated at input: 100-240 VAC / 50-60 Hz, and output: 24 VDC/ 2 A, that can be plugged into an AC outlet, when the device is not in use. Its overall dimensions are 33.6' x 22.6' x 35.8" (855 x 580 x 910 mm). The user can activate the joystick to move in the direction of the joystick is actuated. When the user releases the joystick, the device slows to stop and the brakes are automatically re-engaged. The maximum weight capacity of Joy Rider is 264 lbs. (120 kg) and its maximum speed is 3.75 mph (6 km/h).

I am sorry, but the provided text does not contain information about acceptance criteria and a study proving a medical AI device meets those criteria. The document is a 510(k) submission for an Electrically Powered Wheelchair, named Joy Rider, which is a physical medical device, not an AI-powered diagnostic or therapeutic tool.

The document discusses:

• A 510(k) premarket notification for a powered wheelchair.
• Indications for use, intended user population, and device description.
• Non-clinical performance tests conducted to comply with various ISO and ANSI/RESNA standards relevant to wheelchairs (e.g., static stability, dynamic stability, effectiveness of brakes, speed, obstacle climbing, electromagnetic compatibility).
• Biocompatibility tests for patient-contacting parts.
• A comparison of the subject device (Joy Rider) with a predicate device (Powered Wheelchair, DYW30A(D09)) to demonstrate substantial equivalence, discussing differences in components like motors, wheel sizes, maximum safe operational incline, dimensions, cruising range, and controllers, and asserting that these differences do not raise new safety or effectiveness concerns.

Therefore, I cannot provide the requested information about acceptance criteria and a study for an AI device.

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