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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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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 <=1.77m.

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):

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

• Sample Size for Test Set: Not explicitly stated as this is a device clearance based on standard compliance and comparison, not an image-based AI study with a "test set" in that context. The tests were performed on the physical device models NXN20-208 and NXN20-211.
• Data Provenance: The document states "Non clinical tests were conducted to verify that the proposed device met all design specifications." These tests would have been conducted by the manufacturer (Zhejiang Nysin Medical Co., Ltd.) in China or by a contracted testing facility. The specific location and retrospective/prospective nature of the individual test data are not detailed, but it is implied to be new test data generated for this submission.

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

• Number of Experts: Not applicable. For a powered wheelchair, "ground truth" is typically established through objective measurements and testing against engineering and safety standards, rather than expert consensus on medical images or patient diagnoses.
• Qualifications of Experts: Not applicable for the reasons above. Testing would be performed by qualified engineers and technicians.

4. Adjudication method for the test set

• Adjudication Method: Not applicable. The "test set" here refers to physical device testing against established standards, not a diagnostic task requiring expert 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

• MRMC Study: No, this is not an AI-based diagnostic device. It is a powered wheelchair. Therefore, no MRMC study was conducted, and this question is not applicable.

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

• Standalone Performance: Not applicable. This is not an AI algorithm.

7. The type of ground truth used

• Type of Ground Truth: The "ground truth" for this device is based on objective, quantifiable measurements against internationally recognized performance and safety standards (e.g., ISO 7176 series, IEC 60601-1-2) and visual inspections of the device. For biocompatibility, it's compliance with FDA guidance and ISO 10993-1.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This is not a machine learning or AI device that requires a training set.

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

• Ground Truth for Training Set: Not applicable. There is no training set for this 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 NXN20-205 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 XFGW30-107 and XFGW25-203 Powered Wheelchair is a motor driven, indoor transportation vehicle with the intended use to provide mobility to a disabled or elderly person limited to a seated position. This product is suitable for disabled people with mobility difficulties and elderly people.

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 XFGW30-107 and XFGW25-203 Powered Wheelchair is intended to provide mobility to a disabled or elderly person limited to a seated position.

The provided text is a 510(k) summary for a Powered Wheelchair (K212854). It details the device's characteristics and its comparison to a predicate device to establish substantial equivalence. However, this document does not describe the specific type of study, data, or adjudication methods typically used to prove that an AI/algorithm-based medical device meets acceptance criteria.

The document discusses the regulatory clearance for a physical medical device (a powered wheelchair), not a software or AI-driven diagnostic/therapeutic tool. Therefore, the questions related to AI/algorithm performance, ground truth, expert consensus, MRMC studies, training/test sets, and adjudication methods are not applicable to this document.

The "acceptance criteria" discussed in this document relate to the physical and functional performance of the wheelchair as measured against established ISO standards and comparison to a legally marketed predicate device.

To answer your request based on the provided document, I will reinterpret "acceptance criteria" and "study" in the context of a powered wheelchair's regulatory submission.

Reinterpretation for a Powered Wheelchair:

• Acceptance Criteria: These are the performance and safety requirements that the powered wheelchair must meet, often defined by international standards (e.g., ISO 7176 series) and demonstrated through non-clinical testing.
• Study Proving Acceptance: This refers to the non-clinical testing conducted to show compliance with the standards and substantial equivalence to the predicate device.

Here's the information extracted and reinterpreted where appropriate based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally implied by adherence to the listed international standards (ISO 7176 series, IEC standards, EN 12184, ISO 10993 series). The reported device performance is presented in various sections, particularly in the "Performance Comparison" table (Table 2).

2. Sample Size used for the test set and the data provenance

• Sample Size: The document does not specify a "sample size" in the context of a test set for an algorithm, as this is a physical device. For non-clinical performance and safety testing, typically a certain number of units of the device would be tested to demonstrate compliance with standards. The document states "Non clinical tests were conducted to verify that the proposed device met all design specifications..." but doesn't quantify the number of devices or test repetitions.
• Data Provenance: Not applicable in the sense of patient data for AI. The "data" here comes from a physical product's performance and safety testing.
  • Country of Origin: The manufacturer is Zhejiang Qianxi Vehicle Co., Ltd. (China). Testing would presumably be conducted by the manufacturer or accredited labs.
  • Retrospective or Prospective: Not applicable in the context of an AI study. This is product-specific testing.

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 this context is established by objective measurements and standardized test procedures defined in the ISO and IEC standards, not by human experts interpreting data.

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

• Not applicable. This is for product performance testing against standards, not for human interpretation of data for an AI algorithm.

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 device is a powered wheelchair, not an AI-assisted diagnostic tool. No MRMC study was performed.

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

• Not applicable. This is a physical medical device, not an algorithm.

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

• The "ground truth" for the device's performance is established by the specifications and test methods outlined in objective, internationally recognized standards (e.g., ISO 7176 series for wheelchair performance, ISO 10993 for biocompatibility). The measurements obtained from testing the physical device against these standards serve as the "truth."

8. The sample size for the training set

• Not applicable. This is a physical device, not an AI algorithm. There is no concept of a "training set" for the device itself in this submission.

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

• Not applicable. As above, there is no "training set" for an AI algorithm.

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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 powered wheelchair DYW30A(D09) is driven by two DC motors, and is suitable for indoor uses. It is an individual transportation vehicle for disabled and elderly people that experience difficulties in walking. The powered wheelchair DYW30A(D09) comes as preassembled, designed to be lightweight, easily maneuvered, highly portable, and most importantly, safe and comfortable.

It consists of two foldable armrests, a seat belt, a backrest, a seat cushion, 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 device is powered by two 12 volt / 6 Ah Lithium-ion batteries with 11.2 miles travel range that can be recharged by an off-board battery charger that can be plugged into an AC outlet (110-220 V, 50-60 Hz), when the device is not in use.

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 DYW30A(D09) is 264 lbs and its maximum speed is 3.75 mph.

The provided document is a 510(k) summary for a Powered Wheelchair (DYW30A(D09)). This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than providing a detailed study of an AI/algorithm-based device and its acceptance criteria as requested in the prompt.

Therefore, many of the specific questions regarding acceptance criteria and study methodologies for an AI/algorithm-based device (e.g., sample size for test set, data provenance, number of experts for ground truth, MRMC study, standalone performance, training set details) cannot be answered from the provided text.

The document primarily addresses the safety and effectiveness of a physical medical device (a powered wheelchair) through performance testing against established ISO and IEC standards, and a comparison to a predicate device.

However, I can extract the information relevant to the performance testing and comparison aspects that serve as the "acceptance criteria" for this specific medical device.

Here's what can be extracted based on the provided document:

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

The acceptance criteria for this medical device are based on compliance with a comprehensive set of international standards (ISO and IEC) for wheelchairs. The document reports that the device "passed" these tests, implying compliance with the requirements within those standards. The specific performance values are not always listed as "reported device performance" in a separate row but are implicitly confirmed by passing the tests and in the comparison table.

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

• Sample Size: Not specified for the performance tests. Typically, device testing standards involve a certain number of units or test cycles, but this is not detailed in the summary.
• Data Provenance: The testing was conducted by or on behalf of Nanjing Jin Bai He Medical Apparatus Co., Ltd. in Nanjing, Jiangsu, China. The document is a summary of findings, not raw data. The testing is assumed to be prospective as it's to demonstrate compliance for a new 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 device is a physical product being tested against engineering standards, not an AI/algorithm-based diagnostic tool requiring expert consensus for ground truth. The "ground truth" is established by the specifications and measurement methodologies defined in the listed ISO and IEC standards.

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

Not applicable for physical device performance testing against engineering 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 device is a powered wheelchair, not an AI-assisted diagnostic tool.

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

Not applicable. This is a physical device, not an algorithm.

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

The "ground truth" for this device comes from the established and recognized international standards (ISO and IEC) for wheelchair performance and safety. These standards define the test methods, acceptance limits, and measurement criteria.

8. The sample size for the training set:

Not applicable. This is not an AI/algorithm-based device that requires a training set.

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

Not applicable.

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SOLO+, SOLO and SERVO turn a manually propelled wheelchair into a powered wheelchair. They are intended for medical purposes to provide a means for a disabled person to take over the propulsion of the wheelchair and increase mobility and flexibility.

The subject devices SOLO, SOLO+ and SERVO are power-wheelchair-conversion-kits that add powered propulsion to a manual wheelchair, thereby, turning a manual wheelchair into a powered wheelchair. They consist of two powered wheels (each incorporating an electrical motor) a control unit with its bracket and a battery pack. A battery charger and a bag for the battery pack are included in the delivery as well. The powered wheels substitute the conventional manual wheels from selected wheelchairs. The battery-pack and the controller-unit can easily be attached to the wheelchair. Speed, acceleration and deceleration are microprocessor-controlled. A preselection of the maximum speed can be done with buttons on the control unit. The wheelchair will accelerate or drive with steady speed when the joystick (SOLO and SOLO+) or the hand-rims (SERVO) are pushed into the travel-direction. The motors will steadily reduce the driving force until the wheelchair stops if no driving-signal (deflection of the joystick or the rim) is provided. The safety-brakes lock automatically when the wheelchair stopped (SOLO, SOLO+). The manual parking brakes can also be used to prevent unintended movement. After ten minutes of non-use the device turns off automatically. The powered wheels can be disengaged if the user wants to drive with manual propulsion, only.

The provided document describes the Food and Drug Administration's (FDA) substantial equivalence determination for the AAT Alber Antriebstechnik GmbH's SOLO+, SOLO, and SERVO powered wheelchair conversion kits (K142770). It specifies the devices, their intended use, and a comparison to a predicate device. The document details the non-clinical tests performed to demonstrate substantial equivalence to legally marketed predicate devices, focusing on various ISO standards.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of "acceptance criteria" with specific pass/fail values. Instead, it refers to performing non-clinical tests according to recognized standards. The "reported device performance" is generally stated as meeting these standards or being similar to the predicate device, implying compliance with the standards' requirements.

However, a comparison table and a discussion of differences between the subject device (SOLO / SOLO+ / SERVO) and the predicate device (e-motion, K003449) are provided, which indirectly indicate performance attributes.

Acceptance Criteria (Implied by Standards Met):

The device is deemed to meet acceptance criteria by conforming to the following recognized standards:

• Static stability: ISO 7176-1: Determination of static stability.
• Dynamic stability: ISO 7176-2: Determination of dynamic stability.
• Brake effectiveness: ISO 7176-3: Determination of effectiveness of brakes.
• Power system effectiveness (range): ISO 7176-4: Energy consumption of electric wheelchairs and scooters for determination of theoretical distance.
• Speed, acceleration, deceleration: ISO 7176-6: Determination of maximum speed, acceleration and deceleration of electric wheelchairs.
• Measurement comparability: ISO 7176-7 and ANSI / RESNA WC-1:2009 section 7: method of measurement of seating and wheel dimensions.
• Mechanical strength and durability: ISO 7176-8 Wheelchairs - Part 8: Requirements and test methods for static, impact and fatigue strengths.
• Climatic tests: ISO 7176-9 Wheelchairs - Part 9: Climatic tests for electric wheelchairs.
• Load tests comparability: ISO 7176-11 Wheelchairs - Part 11: Test Dummies.
• Driving and braking tests comparability: ISO 7176-13 Wheelchairs – Part 13 Determination Of Coefficient Of Friction Of Test Surfaces.
• Electrical safety, software-validation and performance: ISO 7176-14 Wheelchairs - Part 14: Power and control systems for electrically powered wheelchairs and scooters -Requirements and test methods.
• Electromagnetic compatibility: ANSI/RESNA wc/ vol.2 and ISO 7176-21 Wheelchairs - Part 21: Requirements and test methods for electromagnetic compatibility of electrically powered wheelchairs and scooters, and battery chargers.
• Biocompatibility: ISO 10993-5: Biological evaluation of medical devices – Part 5: Tests for in vitro cytotoxicity.

The document states that the devices are "as safe, as effective and perform as well as the predicate device" based on these non-clinical tests, implying that the performance meets the necessary standards for substantial equivalence.

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

The document explicitly states that non-clinical tests were performed. These types of tests typically involve testing the physical devices themselves (e.g., a sample of the SOLO, SOLO+, and SERVO models) under controlled laboratory conditions, rather than a "test set" of patient data as might be relevant for AI or diagnostic devices.

The document does not specify the sample size for the devices tested (e.g., number of units of each model).

The data provenance is not explicitly stated as country of origin or retrospective/prospective. However, given that it's a submission to the U.S. FDA by AAT Alber Antriebstechnik GmbH (Germany-based company), the tests were likely performed either in Germany or by a certified testing facility relevant to international standards (ISO). The testing is prospective in the sense that the tests were conducted for the purpose of this submission to demonstrate compliance and substantial equivalence before commercial distribution. It is not retrospective data from real-world usage.

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

This information is not applicable to this type of device and submission. The tests performed are non-clinical, mechanical, electrical, and materials-based assessments against recognized engineering and medical device standards (ISO). There is no "ground truth" derived from expert interpretation of clinical data in the way one would for an AI diagnostic device. The "ground truth" here is the physical performance of the device measured against the established parameters and limits of the ISO standards.

4. Adjudication method for the test set

This information is not applicable for the same reasons as point 3. "Adjudication" typically refers to resolving discrepancies in expert interpretations or clinical outcomes. In non-clinical engineering tests, the results are quantitative measurements against predefined criteria in the 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

This information is not applicable. An MRMC study is relevant for diagnostic devices, particularly those involving human interpretation (e.g., radiologists reading images) where AI assistance might improve their performance. The SOLO+, SOLO, and SERVO are powered mobility devices, not diagnostic or AI-powered devices, and therefore an MRMC study would be irrelevant.

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

This information is not applicable. These devices are not AI algorithms. They are electromechanical devices with microprocessors controlling speed, acceleration, and deceleration, but this is embedded control logic, not a "standalone algorithm" in the context of an AI device. The phrase "algorithm only without human-in-the-loop performance" specifically refers to AI models making decisions independently, which is not what these devices do. They assist a human user in propelling a wheelchair.

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

As discussed in point 3, for these non-clinical tests, the "ground truth" is established by the definitions and quantitative limits within the referenced ISO and ANSI/RESNA standards. For example:

• For static stability (ISO 7176-1), the ground truth is whether the device remains stable at specified angles.
• For brake effectiveness (ISO 7176-3), the ground truth is whether the brakes can stop the device within specified distances or hold it on a specified incline.
• For biocompatibility (ISO 10993-5), the ground truth is the chemical and biological response of materials.

There is no expert consensus on clinical findings, pathology, or outcomes data involved in these specific tests for this device.

8. The sample size for the training set

This information is not applicable. These are not machine learning or AI devices that require a "training set" of data.

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

This information is not applicable as there is no training set.

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The B-500 is rear wheel drive powered wheelchair for active users. These wheelchairs provide mobility to physically challenged persons. The wheelchair can be moved by the user operating the remote control. The wheelchair can also be pushed by an assistant grasping the handles attached to the back rest.
Provide mobility to persons physically challenged and limited to sitting position.

The B-500 Powered Wheelchair is a rear wheel drive powered wheelchair, manufactured in Germany at production facilities of OTTO BOCK HealthCare. The B-500 has an "H" frame, controlled by a P&G Controller, electronic regenerative disc brakes and Micro Motor.

This document does not contain an acceptance criteria table or a study description as typically found for complex medical devices that rely on AI or extensive performance testing against defined metrics.

Instead, this document is a 510(k) summary for a powered wheelchair (B-500 Powered Wheelchair) seeking market clearance through the substantial equivalence pathway. The "study" mentioned for this type of device is usually compliance with recognized international and national standards, rather than a clinical trial or performance study against specific acceptance criteria in the way a diagnostic AI algorithm would be evaluated.

Here's a breakdown of the information that is present in the document, formatted to address your questions where possible:

1. Table of Acceptance Criteria and Reported Device Performance

Explanation: For a powered wheelchair, "acceptance criteria" are typically defined by compliance with established safety and performance standards. The document states that the B-500 was tested by TÜV Product Service to the listed standards, and the conclusion was that "the test sample fulfills the requirements." This indicates that the device met the requirements outlined in these standards, which serve as the de facto acceptance criteria for this type of medical device.

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

This document does not specify a "test set sample size" or "data provenance" in the context of clinical data or AI model evaluation. The "test sample" refers to the physical wheelchair(s) that underwent testing against the specified engineering standards. The typical number of units tested for such compliance would be a limited number of production or prototype units, not a large patient cohort.

• Sample Size: Not explicitly stated, but typically a small number of physical units for engineering standard compliance testing.
• Data Provenance: Not applicable in the context of clinical data. The tests were performed by TÜV Product Service. The manufacturing location is stated as Germany.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not applicable to this document. The "ground truth" for a powered wheelchair's compliance is determined by its adherence to engineering standards and functional performance, not by expert consensus on clinical findings.

4. Adjudication Method for the Test Set

This information is not applicable. The testing was against engineering and safety standards, not a clinical trial requiring adjudication of patient outcomes or interpretations.

5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study

A MRMC comparative effectiveness study was not conducted. This type of study is relevant for diagnostic devices where human readers (e.g., radiologists) interpret images with and without AI assistance. This document describes a powered wheelchair, which is a therapeutic device, not a diagnostic one.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance

Standalone performance, in the context of an algorithm, is not applicable to this device. The B-500 is a physical device, and its performance is evaluated through physical testing against standards, not through an algorithm's output.

7. Type of Ground Truth Used

The "ground truth" for this device's performance is its compliance with established engineering and safety standards (EN 12184, ISO 7176 Series, and ANSI/RESNA WA Vol. 2 Section 21 Amendments 1998 for EMC).

8. Sample Size for the Training Set

This information is not applicable. The device manufacturing process does not involve a "training set" in the context of AI or machine learning.

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

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

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The B-600 is rear wheel drive powered wheelchair for active users. These wheelchairs provide mobility to physically challenged persons. The wheelchair can be moved by the user operating the remote control. The wheelchair can also be pushed by an assistant grasping the handles attached to the back rest.

The B-600 Powered Wheelchair is a rear wheel drive powered wheelchair, manufactured in Germany at production facilities of OTTO BOCK HealthCare. The B-600 has an "H" frame, controlled by Curtis Instruments Controller, electronic regenerative disc brakes, and Micro Motor.

This document is a 510(k) summary for the Otto Bock B-600 Powered Wheelchair. It focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study that proves the device meets specific acceptance criteria in the context of diagnostic accuracy or performance like an AI/ML medical device.

Therefore, many of the requested categories for AI/ML device studies (such as sample sizes for test and training sets, expert qualifications, ground truth establishment, MRMC studies, and standalone performance) are not applicable or extractable from this document.

However, I can extract information related to the demonstration of technological characteristics and standards used.

Device: B-600 Powered Wheelchair

Predicate Device: Quickie Designs (Sunrise Medical) P200 (P220) Wheelchair (K924278)

Here's the information that can be extracted, adapting to the nature of this submission:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not explicitly stated as a numerical count of wheelchairs tested, but it refers to "the test sample" which implies at least one B-600 Powered Wheelchair was subjected to the listed standards.
• Data Provenance: The standards testing was conducted by TÜV Product Service and Montena EMC SA. The device is manufactured in Germany.

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

• Not Applicable. This is a clearance for a powered wheelchair based on performance against established standards and substantial equivalence to a predicate device, not a diagnostic device requiring expert interpretation of results. The "ground truth" here is compliance with engineering and safety standards, determined by testing facilities.

4. Adjudication method for the test set:

• Not Applicable. See point 3.

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/ML 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/ML diagnostic device.

7. The type of ground truth used:

• Compliance with established international and national standards for electric wheelchairs and electromagnetic compatibility (EN 12184, ISO 7176 Series, ANSI/RESNA WA Vol. 2 Section 21 Amendments 1998 for EMC).

8. The sample size for the training set:

• Not Applicable. This is not an AI/ML diagnostic device. There is no concept of a "training set" in this context.

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

• Not Applicable. See point 8.

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The C-1000 is front wheel drive powered wheelchair for active users. These wheelchairs provide mobility to physically challenged persons. The wheelchair can be moved by the user operating the remote control. The wheelchair can also be pushed by an assistant grasping the handles attached to the back rest.
Provide mobility to persons physically challenged and limited to sitting position.

The C-1000 Powered Wheelchair is a front wheel drive powered wheelchair, manufactured in Germany at production facilities of OTTO BOCK HealthCare. The C-1000 has an "H" frame, controlled by a Curtis Instruments MC-2, electronic regenerative disc brakes and Micro Motor.

The provided text describes a 510(k) submission for the Otto Bock C-1000 Powered Wheelchair, seeking clearance for marketing. The nature of this submission and the device itself (a powered wheelchair) means that the "acceptance criteria" and "device performance" are primarily related to safety, functionality, and equivalence to a predicate device, rather than diagnostic accuracy or predictive power as would be seen in a medical imaging AI product.

Therefore, many of the typical acceptance criteria points for an AI/ML device, such as sensitivity, specificity, AUC, and aspects related to human reader studies, are not applicable in this context. The study described focuses on compliance with established engineering and safety standards for wheelchairs.

Here's a breakdown of the requested information based on the provided text, acknowledging the differences due to the device type:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The text states "the test sample" was used, implying one or a small number of C-1000 Powered Wheelchair units were subjected to testing. A specific numerical sample size is not provided.
• Data Provenance: The device was manufactured in Germany at OTTO BOCK HealthCare production facilities. The testing was conducted by TÜV Product Service, an organization based in Europe, which suggests the tests were likely performed in Europe. This was a prospective study, as the tests were conducted specifically for this 510(k) submission.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• This concept is not directly applicable here. The "ground truth" for the performance of a powered wheelchair is its adherence to established engineering and safety standards. The "experts" would be the engineers and technicians at TÜV Product Service who conducted the tests and assessed compliance with the specified standards. Their qualifications would be expertise in mechanical, electrical, and medical device safety testing, and specifically in the standards listed (EN 12184, ISO 7176 Series, ANSI/RESNA WA Vol. 2 Section 21). The number of such individuals is not specified.

4. Adjudication Method for the Test Set

• Not applicable in the context of compliance testing against engineering standards. The results are typically objective measurements against predefined limits or pass/fail criteria within the standards.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is relevant for assessing the impact of a diagnostic aid (often AI-based) on human reader performance, which is not the purpose of this device or its clearance pathway.

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

• Not applicable. The C-1000 Powered Wheelchair is a physical medical device, not an algorithm. Its performance is inherent to the device itself.

7. The Type of Ground Truth Used

• The "ground truth" used for assessing the device's performance was the requirements outlined in the recognized international and national engineering and safety standards:
  • EN 12184 (Electrically-powered wheelchairs)
  • ISO 7176 Series (Wheelchairs)
  • ANSI/RESNA WA Vol. 2 Section 21 Amendments 1998 for EMC (Electromagnetic Compatibility)

8. The Sample Size for the Training Set

• Not applicable. The C-1000 Powered Wheelchair is a physical product designed and manufactured according to established engineering principles, not an AI/ML model that requires a training set.

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

• Not applicable, as there is no training set for this type of device. The design and manufacturing processes are guided by established engineering specifications and quality control measures, which ensure the device's intended characteristics.

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