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The XT2 power wheelchair is a battery-operated device with wheels that is intended for medical purposes to provide mobility to persons restricted to a sitting position who have the capability of operating a power wheelchair. The XT4 power wheelchair is a battery-operated device with wheels that is intended for medical purposes to provide mobility to persons restricted to a sitting position who have the capability of operating a power wheelchair.

The XT Series Power Wheelchair has two configurations: XT2 and XT4. They are designed for everyday use for both indoor and outdoor environments including care facilities and private residences. The subject device is intended to provide mobility to persons who are restricted or limited to a sitting position. The XT Series Power Wheelchairs are battery powered, electric motor driven devices that can be used on both indoor and outdoor surfaces (i.e., concrete, asphalt, indoor flooring such as carpet, gravel, grass, and bark/woodchips). The XT Series Power Wheelchair offers two basic seating options: MPS and Rehab. The MPS option is more static and does not allow for additional aftermarket cushions. The Rehab option is more adjustable to adhere to recommendations from the user's physician or physical therapist.

The provided document is an FDA 510(k) clearance letter and summary for a Magic Mobility XT Series Power Wheelchair. It details the device's technical specifications, indications for use, and a comparison to predicate devices, along with the non-clinical testing performed to establish substantial equivalence.

However, the document does not contain any information about an AI/ML-based medical device, nor does it include details about a study conducted to demonstrate its performance against specific acceptance criteria for such a device. The device described, a powered wheelchair, is a physical medical device, not a software or AI-driven diagnostic or therapeutic tool that would typically have acceptance criteria related to accuracy, sensitivity, specificity, or human-in-the-loop performance improvement.

Therefore, I cannot provide the requested information regarding acceptance criteria and a study proving an AI/ML device meets them, a sample size, expert qualifications, ground truth establishment, or MRMC studies, as these concepts are not applicable to the content of the provided document.

The document focuses on non-clinical bench testing to demonstrate the safety and effectiveness of the physical wheelchair in comparison to existing predicate devices, primarily through adherence to ISO standards for wheelchairs.

To directly answer your prompt, based on the provided text:

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

• This document does not present acceptance criteria or reported performance for an AI/ML device. It lists various ISO standards that the physical wheelchair was tested against. The "reported device performance" is essentially that it met these standards, thus demonstrating substantial equivalence to predicate devices. For example, for "Static stability," the acceptance criterion is compliance with ISO 7176-1, and the reported performance is implicit compliance as it contributed to the substantial equivalence determination.

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

• Not applicable/Not provided for an AI/ML device. The "test set" here refers to the physical wheelchairs undergoing bench testing. The sample size for such physical product testing is not specified, but typically involves a small number of units. Data provenance (country of origin, retrospective/prospective) is not relevant for this type of medical device testing.

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 context of an AI/ML device's performance (e.g., disease detection) is not established for a physical powered wheelchair. The "truth" for this device is its adherence to engineering standards.

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

• Not applicable. This is a concept for reconciling disagreements among human readers in a diagnostic AI/ML study, not for physical product testing.

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, an MRMC study was not done as this is a physical wheelchair, not an AI/ML diagnostic or assistive device.

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

• Not applicable. There is no AI algorithm being submitted for standalone performance evaluation in this document.

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

• Not applicable in the context of AI/ML. The "ground truth" for this device's performance is adherence to established international engineering and safety standards (e.g., ISO, IEC).

8. The sample size for the training set:

• Not applicable. This document does not describe an AI/ML device, so there is no training set for an algorithm.

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

• Not applicable for the same reason as above.

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The Frontier Series Power Wheelchairs are battery-operated devices with wheels that are intended for medical purposes to provide mobility to persons restricted to a sitting position who have the capability of operating a power wheelchair.

The Frontier Series Power Wheelchairs have four configurations: V4 RWD, V4 FWD, V6, and C73. The Frontier Series Power Wheelchairs are designed for everyday use for both indoor and outdoor environments including care facilities and private residences. The subject devices are intended to provide mobility to persons who are restricted or limited to a sitting position. The Frontier Series Power Wheelchairs are battery powered, electric motor driven devices that can be used on both indoor and outdoor surfaces (i.e., concrete, asphalt, indoor flooring such as carpet, gravel, grass, and bark/woodchips).

This is a 510(k) premarket notification for the "Frontier Series Power Wheelchairs". This document is a submission to the FDA to demonstrate that the new device is "substantially equivalent" to already legally marketed predicate devices. Therefore, the "acceptance criteria" here refers to the performance of the device relative to established standards and the predicate devices, rather than strict statistical thresholds for an AI algorithm.

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

The acceptance criteria are established by adherence to recognized international standards and comparison to predicate devices, showing that any differences do not affect safety or effectiveness. The reported device performance is demonstrated by meeting these standards and having similar or identical characteristics to the predicate devices.

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

This submission describes non-clinical performance and engineering testing on the device prototypes, not a clinical study on human subjects with a test set of data in the traditional sense of an AI/imaging device. The "test set" would be the physical Frontier Series Power Wheelchairs themselves, subjected to various standardized tests. No specific numerical sample size (e.g., how many wheelchairs were tested for each test) is provided in the document, other than implying the testing of "the subject devices." The provenance is manufacturing in Australia. The testing is presumably prospective for the purpose of this 510(k) submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This is not applicable to this type of device submission. Ground truth, in the context of this 510(k), refers to the established standards (e.g., ISO 7176 series, ISO 10993 series, IEC 62304) and the performance characteristics of the predicate devices. The "experts" are the creators of these standards, and the engineers/testers who conduct measurements and compare the device's performance against these benchmarks and the predicate devices' specifications. No specific number or qualifications of such 'experts' are provided in this document beyond the general statement of "testing performed."

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

This is not applicable. The evaluation is based on objective measurements against engineering standards and comparison of technical specifications to predicate devices, not subjective assessments requiring adjudication by multiple readers.

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 as the device is a power wheelchair, not an AI-assisted diagnostic or therapeutic tool that involves human readers or interpretation of medical cases.

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

This is not applicable. This is a physical medical device (power wheelchair), not an algorithm or AI system.

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

The "ground truth" for this submission is established by:

• International Standards: Complying with numerous ISO and IEC standards for wheelchairs (e.g., ISO 7176-1 for static stability, ISO 10993-1 for biocompatibility, IEC 62304 for software life cycle).
• Predicate Device Performance: Demonstrating that the subject device's technological characteristics and performance are similar or identical to legally marketed predicate devices, or that any differences do not raise new questions of safety or effectiveness.

8. The sample size for the training set

This is not applicable as the device is a physical power wheelchair, not an AI algorithm trained on a dataset. The design and manufacturing process would involve engineering iterations and testing, but not a "training set" in the context of machine learning.

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

Not applicable. As described above, this is about adherence to engineering standards and comparison to predicate devices, not machine learning ground truth.

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The Extreme X8 Power Wheelchair is a battery-operated device with wheels that is intended for medical purposes to provide mobility to persons restricted to a sitting position who have the capability of operating a power wheelchair.

The Extreme X8 Power Wheelchair is designed for everyday use for both indoor and outdoor environments including care facilities and private residences. The subject device is intended to provide mobility to persons who are restricted or limited to a sitting position. The Extreme X8 Power Wheelchair is a battery powered, electric motor driven device that can be used on both indoor and outdoor surfaces (i.e., concrete, asphalt, indoor flooring such as carpet, gravel, grass, and bark/woodchips).The Extreme X8 Power Wheelchair offers two basic seating options: MPS and Rehab. The MPS option is more static and does not allow for additional aftermarket cushions. The Rehab option is more adjustable to adhere to recommendations from the user's physician or physical therapist.

The provided text is a 510(k) summary for a powered wheelchair, not an AI/ML medical device. Therefore, the information requested in the prompt, which is specific to AI/ML device studies (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC studies, standalone performance, training set sample size), is not applicable and cannot be extracted from this document.

The document discusses the substantial equivalence of the "Extreme X8 Power Wheelchair" to a predicate device, focusing on non-clinical testing for performance, EMC and electrical safety, biocompatibility, and software in the context of general medical device safety and effectiveness.

Here's a breakdown of the relevant information provided, tailored to the context of a non-AI/ML medical device for which the prompt's questions are not appropriate:

1. Acceptance Criteria and Reported Device Performance:

The acceptance criteria are implicitly defined by compliance with various ISO standards for wheelchairs. The reported device performance is that the "Extreme X8 Power Wheelchair has undergone testing to ensure that any differences in technological characteristics (i.e., battery, castor wheels, and no anti-pitch mechanism) do not affect safety and effectiveness when compared to the predicate device."

The study proving the device meets these criteria is the non-clinical testing summarized in the "Summary of Non-Clinical Testing" section. This testing demonstrated that the Extreme X8 Power Wheelchair does not raise new issues of safety or effectiveness compared to the predicate device, leading to a conclusion of substantial equivalence.

The following numbered points from the prompt cannot be answered as they pertain to AI/ML device studies, and this document is for a physical medical device (powered wheelchair):

2. Sample sizes used for the test set and the data provenance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts.
4. Adjudication method for the test set.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc).
8. The sample size for the training set.
9. How the ground truth for the training set was established.

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The Magic 360 Power Wheelchair is a battery-operated device with wheels that is intended for medical purposes to provide mobility to persons restricted to a sitting position who have the capability of operating a power wheelchair.

The Magic 360 Power Wheelchair is designed for everyday use for both indoor and outdoor environments including care facilities and private residences. The subject device is intended to provide mobility to persons that are restricted or limited to a sitting position.

The Magic 360 Power Wheelchair is a battery powered, electric motor driven device that can be used on both indoor and outdoor surfaces (i.e. concrete, asphalt, indoor flooring, gravel, grass, and bark). The subject device has two seat options: MPS and rehab. The rehab seat option has more built-in adjustments (i.e., width and depth adjustments) and allows for aftermarket cushions. All the wheelchairs include the same power seating options including lift, tilt, recline, and leg elevation to ensure the user to find a position that is comfortable.

The Magic 360 Power Wheelchair includes the following accessories:

• Extra spreader bar
• Slide in table
• Lights
• Luggage rack
• Accessory charger ●
• Posture belt
• Roho cushion
• Jay cushion
• MPS push rail
• MPS peg push handle
• Scooter stopper ●
• Retractable docking pin
• Fold forward kit

Please note, the fold forward kit is an accessory which allows the user to fold the wheelchair and put the wheelchair in a car. To fold the wheelchair the user pulls the red release handle located at the back of the Magic 360 Power Wheelchair. To unfold the wheelchair the user pulls the frame back into place using the armrests.

The provided text is a 510(k) summary for the Magic 360 Power Wheelchair. This document is a regulatory submission to the FDA for medical device clearance, not a study evaluating an AI algorithm's performance. Therefore, most of the requested information regarding acceptance criteria and a study proving device meets acceptance criteria is not directly applicable in the AI/ML context.

However, I can extract the closest analogous information from the document as it pertains to a traditional medical device (power wheelchair).

Here's an interpretation based on the provided text:

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

The document does not present a table of specific acceptance criteria with quantitative performance metrics for the Magic 360 Power Wheelchair in the way one would for an AI algorithm (e.g., sensitivity, specificity thresholds). Instead, the "acceptance criteria" are implied by adherence to recognized ISO standards for wheelchairs and demonstrating substantial equivalence to predicate devices. The "reported device performance" is inferred from the successful completion of these tests.

The comparison table provided in the document (pages 6-7) highlights the characteristics of the Magic 360 Power Wheelchair against predicate devices. The "Statement of Equivalence" column implicitly indicates that the device's performance characteristics are either identical or substantially equivalent to the predicate devices, thus meeting regulatory expectations.

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 because this is a submission for a physical medical device (power wheelchair) and not an AI/ML algorithm. The "test set" in this context refers to physical units of the wheelchair undergoing standardized engineering and performance tests, not a dataset for an algorithm. There is no mention of "data provenance" in the sense of patient data. The manufacturer is based in Australia ("3 International Court, Scoresby, VIC, 3179 Australia").

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This is not applicable to this type of device submission. "Ground truth" in this context would implicitly be the established engineering specifications and performance requirements defined by ISO standards and regulatory guidelines, confirmed through physical testing by qualified engineers or technicians.

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

Not applicable. This concept relates to human review of data, which is not described for the performance testing of this physical device. The testing described (e.g., Static stability, Dynamic stability, EMC testing) are objective engineering measurements against defined 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

Not applicable. This is not an AI-assisted device.

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

Not applicable. This is not an AI algorithm.

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

The "ground truth" for this medical device's performance is established by international consensus standards (ISO standards) for wheelchairs regarding functionality, safety, and durability, as well as the performance characteristics of legally marketed predicate devices. The testing verifies that the device performs according to these objective standards and is comparable to equivalent devices already on the market.

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no "training set." The device is designed, manufactured, and tested to engineering specifications.

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

Not applicable, as there is no training set mentioned in the context of an AI/ML algorithm.

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The F5 Corpus VS powered wheelchair is to provide indoor mobility, including stand-up feature, to persons limited to a seating position that are capable of operating a powered wheelchair.

F5 Corpus VS Powered Wheelchair is battery powered, front wheel motor driven and is controlled by the R-net 120 amp controller. The user interface is a joystick. The F5 Corpus VS is powered by two 12VDC, Group M24, approximate driving range on fully charged batteries is up to 25km (15.5 miles), depending on use and the terrain the chair is driven on. The chair frame is a steel construction and includes two front drive units (motor, gear and brake), two batteries and two rear pivoting casters. Depending on the user's needs, the joystick motor control is mounted to the left or right armrest. When the user activates the joystick, the controller receives a signal to release the brakes. With the brakes released, the chair is allowed to move in the joystick is actuated. When the user releases the joystick, the chair slows to a stop and the brakes are automatically re-engaged. The solenoid electromechanical brakes allow the user to stop by letting go of the joystick. F5 Corpus VS will enable the user to stand up, completely or partially, to facilitate reaching, working eye to eye with colleagues. The standing sequence is controlled by the joystick and gives the user the possibility to come to a standing position. The seating, chest support and knee stop stabilize the user during the stand-up or sitdown operation.

This document (K191874) is a 510(k) premarket notification for a powered wheelchair, the F5 Corpus VS. It compares the device to two predicates: the Quickie® Q700-UP M (K172384) and the F5 (K143014).

Based on the provided text, here is an analysis of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally demonstrated by compliance with various ISO and RESNA standards for wheelchairs. The document does not present a single table explicitly listing "acceptance criteria" against "reported device performance" in a quantitative manner for all aspects. Instead, it states compliance with standards and provides some performance specifications when comparing the device to its predicates.

Here's an attempt to compile relevant information, though a direct "acceptance criteria" column is not explicitly defined in the document for each performance characteristic:

The document emphasizes that the F5 Corpus VS passes the requirements in ISO 7176 and RESNA WC-1:2009 Section 20.

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

The document refers to "Non-Clinical Testing" which involves compliance with a long list of ISO standards and RESNA WC-1. These are physical performance tests for the device itself (e.g., stability, brake effectiveness, strength).

• Sample size for the test set: Not explicitly stated as a number of devices or units. Typically, for device performance testing against standards, a representative sample (e.g., a few units or prototypes) is tested. The nature of these tests does not involve patient data or human subjects for the "test set" in the context of an AI/algorithm study.
• Data provenance: Not applicable in the context of patient data for an algorithm. The tests are for the physical wheelchair device. The Permobil AB company is based in Sweden. The tests were conducted to international standards.

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 applicable as the device is a physical powered wheelchair, not an AI/algorithm that requires expert-established ground truth from medical images or patient data. The "ground truth" here is the physical performance of the device as measured by standardized engineering and safety tests.

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

This information is not applicable as the device is a physical powered wheelchair, not an AI/algorithm study involving adjudication of clinical findings. Compliance with standards is typically measured objectively through specified test procedures.

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 information is not applicable. The device is a physical powered wheelchair. There is no AI component or human reader in the context of medical image interpretation that would warrant an MRMC study.

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

This information is not applicable. The device is a physical powered wheelchair, not a standalone algorithm.

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

The "ground truth" for the F5 Corpus VS device is its physical performance, safety, and functional characteristics as measured and validated against established international standards (ISO 7176 series and RESNA WC-1:2009 Section 20). These standards define objective test methods and acceptable performance limits.

8. The sample size for the training set

This information is not applicable. The device is a physical powered wheelchair. There is no AI/algorithm being trained on a dataset. The design and manufacturing process would involve engineering principles and testing, not machine learning training.

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

This information is not applicable for the same reasons as in point 8.

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The UPnRIDE™ stand-up power wheelchair is intended for medical purposes to provide mobility to persons restricted to a sitting position. The product changes position from Sitting to Standing and Standing to Sitting but also any position in between. The product provides indoor and outdoor mobility.

The UPnRIDE™ device enables disabled and elderly individuals to be mobile in a sitting or standing position indoors and outdoors. The device design is based on the following principles: 1. Using motorized jointed braces and harnessing to safely support the user while sitting, shifting to standing, standing and returning to sitting - 2. Center of gravity (COG) is maintained substantially at the center of the device in all positions, thus maximizing stability and safety. - 3. Balancing the platform which supports the user so that the user always remains vertical even on skewed surfaces. - 4. Implementing an operation and safety algorithms to minimize risks and hazards to the user, even beyond the provisions of standard wheelchairs. The product is comprised of the following modules: - Driving module: a motorized driving chassis that 1. includes two front motorized wheels, two high capacity Li-Ion batteries 21.6VDC / 29.7Ah and a steel frame which is installed as a chassis for the device's components. - Inertial Measurement Unit ("IMU") for measuring 2. ground slopes (pitch and roll) and user's tilt angles (pitch and roll). - Standing and sitting module: a motor-based lifting 3. mechanism for shifting between standing and sitting positions. - 4. Balancing module: a platform that balances the user while sitting or standing, relative to earth. - 5. User interface module: a unit through which the user controls the UPnRIDE™. This module has an "R-NET" controller that contains a Joystick, commanding buttons and a display for viewing indications and status and a switching box for controlling the various modes of operation. - Actuator drivers: five units that control the lifting 6. motors. - 7. Main Controller: a unit which reads all sensors and user inputs, performs the balancing and safety algorithms, and controls all the chairs function.

The provided text is a 510(k) summary for the UPnRIDE stand-up power wheelchair. It does not contain information about acceptance criteria and a study proving the device meets those criteria in the context of an AI/ML device.

Instead, the document focuses on demonstrating substantial equivalence to predicate devices (Levo Comfort II and Quickie Q700-UP M) by comparing intended use, technical characteristics, and adherence to performance standards.

Here's how the requested information relates to the provided text:

• Acceptance Criteria and Reported Device Performance: This information is not present for an AI/ML component. The text lists voluntary standards (ISO series, ANSI/RESNA WC-1) that the UPnRIDE complies with, which are performance standards for wheelchairs in general, not specific acceptance criteria for an AI/ML algorithm's output.
• Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not applicable, as there's no AI/ML test set discussed. The document mentions "performance tests" and a "usability study" but provides no details on sample size, data provenance, or methodology for these.
• 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.
• Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The device is a physical wheelchair with an "operation and safety algorithms" and a "Main Controller" that "performs the balancing and safety algorithms," but these are embedded control systems, not a standalone AI/ML diagnostic or predictive algorithm being evaluated for performance against a ground truth dataset in the way typically discussed in AI/ML reviews.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable for an AI/ML component. The mention of "balancing operation was validated by multitude performance tests and a usability study" suggests physical performance and user experience were evaluated, not AI/ML output.
• The sample size for the training set: Not applicable.
• How the ground truth for the training set was established: Not applicable.

In summary, the provided document is a 510(k) premarket notification for a stand-up power wheelchair and does not include the type of detailed information about acceptance criteria and studies for an AI/ML device as requested. It focuses on demonstrating substantial equivalence to existing medical devices through technical comparison and compliance with relevant industry standards for wheelchairs.

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