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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 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.

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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 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.

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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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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 Electrically Powered Wheelchair - Model HP358E is powered by Li-ion battery, driven by DC motor. Users control direction and adjust speed by controller. The main frame of the wheelchair is made of aluminum alloy. It has a seat base with four-wheeled and two with a back cover on the frame. Wheels are connected to the stainless steel axle receivers via stainless steel axles. On the front end of the frame are assembled two caster housings. Caster forks are mounted to these housings via steel axles. There are two rear caster wheels in back and anti-tip wheels in front to prevent the power chair from tipping. On the front end of the frame, upon the caster, a foot platform is assembled for foot holding. Two non-adjustable armrests are mounted on the frame for user's arm holding. Two grips mounted on the top end of the frame with a brake, and another brake is designed under the seat base. The backrest can be adjusted by squeezing yellow catches on the back together. A storage compartment located between the seat and foot platform. The joystick can be mounted on the left or right side using the quick release mechanism. The subject device has two 2 inch Anti-tippers, two 8 inch front wheels and two 12 inch rear wheels. The motor is DC24V 250W; the battery is 25.2 V 10.4Ah Li-ion battery; the charger is DC 24V, 2A. Max. loading can not be over than 125Kg, the maximum distance of travel on the fully charged battery is 10km and its maximum speed is 6km/h. The braking time is about 2~3s, and the braking distance is ≤1.0m.

The provided text is a 510(k) Summary for an Electrically Powered Wheelchair (Model HP358E). It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study of a device's performance against specific acceptance criteria in the context of AI or advanced diagnostic algorithms. Therefore, much of the requested information regarding AI device evaluation (e.g., sample size for test set, provenance, expert adjudication, MRMC studies, standalone performance, training set details) is not applicable or present in this document.

However, I can extract the relevant "acceptance criteria" (which in this context are performance and safety standards) and the "device performance" as reported for the proposed device, along with other applicable details.

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

The "acceptance criteria" for this wheeled device are derived from various ISO and IEC standards that it claims to comply with, and the "reported device performance" are the measured specifications of the HP358E. These are primarily found in the "Non-Clinical Test Summary" and the "Performance Comparison" table.

Acceptance Criteria & Reported Device Performance for Electrically Powered Wheelchair - Model HP358E

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

This document describes the testing of a physical medical device (an electrically powered wheelchair) against engineering and safety standards. The "test set" here refers to the actual device prototypes or samples subjected to the described non-clinical tests. The number of individual devices tested is not specified, but it's standard practice in such non-clinical testing to test a representative sample size to ensure reliability and repeatability according to the testing standards (e.g., ISO and IEC).

• Sample Size: Not explicitly stated for each test, but implied to be a sufficient number of device units to perform the required non-clinical tests according to the cited ISO/IEC standards.
• Data Provenance: The tests are non-clinical engineering and safety performance tests, not clinical data from patients. The document does not specify the location where these tests were performed, but the manufacturer is based in China. The data would be derived from the physical testing of the device.

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

This is not applicable as the "ground truth" for non-clinical performance and safety of a wheelchair is established by the objective measurements against established international engineering and safety standards (ISO, IEC, EN). There are no "experts" establishing a "ground truth" in the way radiologists establish ground truth for an AI diagnostic algorithm; rather, the device's performance is measured and compared against the limits and criteria defined by the standards.

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

This is not applicable for non-clinical engineering and safety tests. Adjudication methods like 2+1 or 3+1 are used for establishing ground truth in clinical imaging studies, particularly for AI device evaluations where human expert consensus is required for labeling data.

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. The device is an electrically powered wheelchair, not an AI-powered diagnostic tool, and therefore, no MRMC study or AI assistance evaluation was performed or is relevant.

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

This is not applicable. The device is a physical medical device, not an algorithm, so the concept of standalone algorithm performance is irrelevant.

7. The type of ground truth used:

The "ground truth" for the device's performance and safety is derived from established international engineering and safety standards (ISO, IEC, EN). The device's physical and functional attributes were measured and assessed to ensure they comply with the stipulated requirements of these standards. For biocompatibility, the ground truth is established by adherence to ISO 10993 series standards and related FDA guidance, with specific tests like cytotoxicity, irritation, and skin sensitization. For software, the ground truth for its safety and functionality is established through validation against FDA guidance for "Moderate Level of Concern" software.

8. The sample size for the training set:

This is not applicable. The document does not describe an AI/ML device that requires a training set.

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

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

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