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The manual wheelchair is to provide mobility to persons limited to a sitting position.

Manual Wheelchair (HM305-Air1, HM305-Air2)

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The manual wheelchair is to provide mobility to persons limited to a sitting position.

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The Manual Wheelchair is to provide mobility to persons limited to a sitting position.

The S002, S004, S005, S006, S007, S008, S009 series are mechanical wheelchairs which are a manually operated devices with wheels that are intended for medical purposes to provide mobility to persons restricted to a sitting position. It can be folded for transport by bring the two sides together. The manual wheelchair incorporates a main frame, a seat, two adjustable footrests and four wheels. The larger rear wheels have hand rims of slightly smaller diameter projecting just beyond the tire. These allows the user to manoeuvre the chair by pushing them on without requiring them to grasp the tires. The manual wheelchairs have brakes that bear on the tires of the rear wheels and two push handles at the upper rear of the frame to allow for manual propulsion by an assistant.

Main Components: Main frame, Backrest, Seat cushion, handgrip, front wheel, rear wheel, hand rim, crossbar, footrests, brake, Anti-tipper, Seat belt.

The device can be operated indoors, or outdoors on dry, level surfaces composed of concrete, blacktop, or asphalt under normal driving conditions.

This FDA 510(k) summary describes a Manual Wheelchair (Models: S002, S004, S005, S006, S007, S008, S009) and its substantial equivalence to a predicate device (K232230). The information provided is for a physical medical device, not an AI/software device. Therefore, many of the requested categories related to AI/software performance criteria (such as sample sizes for test/training sets, data provenance, expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance) are not applicable to this document.

However, I can extract the acceptance criteria related to the physical device's performance and the study details that demonstrate it meets those criteria.

1. Table of acceptance criteria and the reported device performance:

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

• Sample size: Not specified in the document. For physical device performance testing, samples are typically a representative number of units, but specific numbers are not usually detailed in a 510(k) summary unless a specific statistical power is claimed for a particular test.
• Data provenance: The tests were conducted by the applicant, Anhui JBH Medical Apparatus Co., Ltd, in China (No.116 QiCang Road Industrial District MingGuang Chuzhou,Anhui, China). The data is retrospective in the sense that the tests were performed on finished devices to demonstrate compliance.

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. For physical device performance, "ground truth" is established through standardized testing procedures and objective measurements as defined by the referenced ISO standards, not through expert consensus on interpretation.

4. Adjudication method for the test set:

Not applicable. Physical device performance is determined by meeting objective criteria defined in the ISO standards, not by an adjudication process as used in clinical or imaging studies.

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 a physical medical device, not an AI/software device.

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 AI/software device.

7. The type of ground truth used:

The "ground truth" for the device's performance is established by its adherence to the technical specifications and performance limits defined within the cited international ISO standards (e.g., ISO 7176 series for wheelchairs and ISO 10993 series for biocompatibility). This is essentially objective measurement against predefined engineering and biocompatibility standards.

8. The sample size for the training set:

Not applicable. This is a physical medical device, not an AI/software device that requires a training set.

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

Not applicable. This is a physical medical device, not an AI/software device.

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The Manual Wheelchair is to provide mobility to persons limited to a sitting position.

The MASY23 manual wheelchair is a mechanical wheelchair which is a manually operated, attendant and self-propelled transport device in a health care environment such as a hospital, nursing home or extended care facility. It is intended for medical purpose to provide mobility to persons limited to a sitting position. It can be folded for transport by bring two sides together.

The MASY23 Manual Wheelchair incorporates a main frame, a seat, two hand rims and four wheels. The wheelchair is designed with two small rear wheels and two gearing with hand rim, it can be manually moved forward and in reverse. The wheelchair can support users of up to 136 kg.

The provided text is a 510(k) Premarket Notification from the FDA regarding a Manual Wheelchair (MASY23). It does not describe a study, acceptance criteria, or performance data for an AI/ML-driven medical device.

Therefore, I cannot extract the requested information regarding acceptance criteria, study details, sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, training set details, or how ground truth was established, as these concepts are not applicable to the clearance of a manual wheelchair.

The document focuses on demonstrating substantial equivalence of the manual wheelchair to a predicate device through non-clinical performance and biocompatibility testing, primarily against ISO standards.

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The SYIV100-CA9221 manual wheelchair is to provide mobility to persons limited to a sitting position

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I am sorry, but the provided text from the FDA 510(k) clearance letter for the "Manual Wheelchair (SYIV100-CA9221)" does not contain any information about acceptance criteria or a study that proves the device meets specific performance criteria.

The 510(k) process for a mechanical wheelchair, as is the case here (Regulation Number: 21 CFR 890.3850, Product Code: IOR), focuses on demonstrating substantial equivalence to a predicate device. This typically involves comparing features, specifications, and sometimes basic functional tests to ensure the new device performs as safely and effectively as a legally marketed predicate.

The document is a standard FDA clearance letter and discusses:

• The determination of substantial equivalence.
• General controls and regulations applicable to the device (e.g., annual registration, listing, GMP, labeling, UDI).
• Contact information for various FDA departments.
• The indications for use of the wheelchair: "to provide mobility to persons limited to a sitting position."

It does not contain the type of AI/algorithm performance study information you are asking for, which would be typical for a software as a medical device (SaMD) or AI-powered medical device clearance.

Therefore, I cannot populate the requested table or answer your specific questions about acceptance criteria, study design, expert consensus, ground truth, or MRMC studies based on the provided text. This document is for a simple mechanical device, not an AI or algorithm-driven one.

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The Manual Wheelchair is to provide mobility to persons limited to a sitting position.

MW18 manual wheelchair is a mechanical which is a manually operated device with wheels that is intended for medical purposes to provide mobility to persons restricted to a sitting position. It can be folded for transport by bring the two sides together. The manual wheelchair incorporates a foldable frame, a seat, two footrests and four wheels. The larger rear wheels have push-rims of slightly smaller diameter projecting just beyond the user to manoeuvre the chair by pushing them on without requiring them to grasp the tyres. The manual wheelchairs have brakes that bear on the tyres of there are two push handles at the upper rear of the frame to allow for manual propulsion by a second person, e.g. caregiver. The wheelchair can support users of up to 120kg.

Main Components:

Main frame, back upholstery, seat upholstery, handgrip, armrest, front wheel, hand rim, crossbar, footrest, skirt guard, brake, anti-tipper (optional)

The device can be operated indoors, or outdoors on dry, level surfaces composed of concrete, blacktop, or asphalt under normal driving conditions.

The provided FDA 510(k) summary is for a Manual Wheelchair (MW18), a Class I, reserved medical device. This type of device does not typically involve AI components or require the complex statistical studies, multi-reader multi-case studies, and expert ground truth establishment that are common for AI/ML-driven diagnostic devices.

Instead, the acceptance criteria for a manual wheelchair primarily focus on functional performance, safety, and compliance with established industry standards. The study proving the device meets these criteria is a series of non-clinical performance tests conducted in accordance with international standards for wheelchairs.

Here's the breakdown of the information requested, based on the provided document:

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

The document lists the ISO standards that the device complies with, which effectively serve as the acceptance criteria. The "reported device performance" is the statement of compliance with these standards.

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

The document does not specify a "test set" in the context of patient data, as this is a mechanical device. The "test set" refers to the physical units of the Manual Wheelchair (MW18) that were subjected to the non-clinical tests. The document does not explicitly state the number of sample units used for these tests. Data provenance is not applicable in the context of patient data as it's not an AI/ML device.

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 device. "Ground truth" in the context of AI/ML performance is not relevant for a mechanical manual wheelchair. The "truth" is established by the ability of the device to meet the defined performance specifications and safety standards through physical testing.

4. Adjudication method for the test set

This information is not applicable. Adjudication methods like 2+1 or 3+1 are typically used for establishing ground truth in clinical image interpretation, not for mechanical device testing. Compliance with standards is typically assessed by conformity to predefined pass/fail criteria for each test.

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. An MRMC study is designed for evaluating the performance of diagnostic algorithms, often with human readers in the loop. This device is a manual wheelchair, not a diagnostic AI tool.

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

This is not applicable. This is a mechanical device, not an algorithm.

7. The type of ground truth used

The "ground truth" for this device is the compliance with established international performance and safety standards (ISO standards) for manual wheelchairs. This is determined through objective, quantifiable physical tests, rather than expert consensus, pathology, or outcomes data in the way it's understood for diagnostic devices.

8. The sample size for the training set

This is not applicable. There is no "training set" for a mechanical device like a manual wheelchair.

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

This is not applicable. There is no "training set" or "ground truth for a training set" for this type of device.

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The A006 Manual Wheelchair is to provide mobility to persons limited to a sitting position.

The subject device is a mechanical wheelchair which is a manually operated device with wheels that is intended for medical purposes to provide mobility to persons restricted to a sitting position. It can be folded for transport by bringing the two sides together. The manual wheelchair incorporates a main frame, a seat, two adjustable footrests and four wheels. The larger rear wheels have hand rims of slightly smaller diameter projecting just beyond the tire. These allows the user to maneuver the chair by pushing them on without requiring them to grasp the tires. The manual wheelchairs have brakes that bear on the tires of the rear wheels and two push handles at the upper rear of the frame to allow for manual propulsion by an assistant.

This document describes the FDA's clearance of a Manual Wheelchair (Model A006) and is a 510(k) Premarket Notification. The purpose of a 510(k) submission is to demonstrate that a new device is "substantially equivalent" to a legally marketed predicate device. This process differs significantly from studies that prove a medical device, especially AI/ML-driven software, meets specific performance acceptance criteria through clinical or non-clinical trials.

Therefore, the provided text does not contain the information required to answer the prompt. It is a regulatory clearance document for a mechanical device, not a study evaluating the performance of an AI/ML device against acceptance criteria.

Here's why the prompt cannot be answered with this document:

• No AI/ML device: The device in question is a manual wheelchair, a physical, mechanical product. There is no software, AI, or algorithm involved.
• No "acceptance criteria" in the AI/ML performance sense: The "acceptance criteria" here refer to meeting regulatory standards for safety and effectiveness in comparison to a predicate mechanical device (another wheelchair), not to the performance metrics (like accuracy, sensitivity, specificity, AUC) typically established for AI/ML devices.
• No "study" in the AI/ML performance sense: The document describes non-clinical performance testing against established ISO standards for wheelchairs (e.g., static stability, brake effectiveness, dimensions, strength). It explicitly states, "No clinical study is included in this submission." There are no human readers, ground truth establishment, training sets, test sets, or MRMC studies as would be relevant for an AI/ML device.

To answer the prompt, a document describing the development and validation of an AI/ML-driven medical device, including performance data from a clinical or non-clinical study, would be necessary.

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The Manual Wheelchair is intended for medical purposes to provide mobility to persons restricted to a sitting position.

The Manual Wheelchair is a wheeled personal mobility device that incorporates a seat-support system for a person with a disability or a person without the full capacity to walk designed to be manually propelled by the user while seated in the device or by an attendant. The occupant moves the wheelchair by rotating two handrims protruding from rear wheels. An attendant moves the device by pushing or pulling handles on the device. The device can be folded for transport. The device can be operated indoor or outdoor on dry, smooth surfaces composed of concrete, blacktop or asphalt under normal driving conditions. The subject manual wheelchair is a mechanical wheelchair with four wheels, including two front casters and two rear wheels, a frame made of carbon steel, a seat and a backrest made of oxford fabric, which is soft and water-resistant, two handles, armrests, handrims, foot pedals, legrest strap and seat belt. The subject manual wheelchair has a physical dimension of 1085mm × 700mm ×935mm (length × width × height). The device has a weight capacity of 100 kilograms, and its total mass is 17.3kg. The color is black.

This document describes the premarket notification (510(k)) for a Manual Wheelchair (Model: SYIV100-RLD-G01) seeking clearance from the U.S. Food and Drug Administration (FDA).

It's important to note that this is a Class I medical device (Mechanical Wheelchair, Product Code: IOR), which are generally considered low risk and do not require extensive clinical trials or complex AI performance criteria as seen with higher-class devices. The primary method for proving substantial equivalence for such devices is often through non-clinical performance testing and comparison to an existing predicate device.

Therefore, many of the typical "AI device" specific questions (like MRMC studies, training set details, or expert consensus for ground truth) are not applicable to this specific submission, as the device is not an AI-powered diagnostic or therapeutic tool. The "acceptance criteria" here refer to the device meeting established performance standards for manual wheelchairs, rather than AI performance metrics.

Here is the information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

For this manual wheelchair, the acceptance criteria are based on compliance with recognized performance and safety standards, and demonstrating that the proposed device performs "as well as" a legally marketed predicate device. The document does not present a formal "table of acceptance criteria and reported device performance" as one might see for an AI algorithm with metrics like sensitivity/specificity. Instead, it demonstrates compliance through adherence to ISO standards and a comparative analysis.

Acceptance Criteria (Implicit: Compliance with Standards and Predicate Equivalence)

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

• Test Set Sample Size: Not explicitly stated as a "sample size" in terms of number of patients or images, because this is a physical medical device. The "test set" here refers to the physical units of the manual wheelchair subjected to various engineering and biocompatibility tests. Typically, a small number of units (e.g., 1-3) are tested to demonstrate compliance with standards for Class I devices like this.
• Data Provenance: The tests are non-clinical (laboratory and engineering tests) conducted on the manufactured device. The geographic origin of the testing is not specified, but the manufacturer is based in China. The data would be considered prospective in the sense that the tests were performed specifically for this 510(k) submission.

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 this type of device submission. There is no "ground truth" established by human experts in the context of diagnostic or AI performance for a manual wheelchair. The "ground truth" for this device's performance is objective measurements against established engineering and biocompatibility standards.

4. Adjudication method for the test set

• This is not applicable. No adjudication method (like 2+1, 3+1 consensus) is relevant for non-clinical engineering and biocompatibility testing of a physical product like a manual wheelchair.

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. This is not an AI device or an imaging device requiring human reader studies.

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

• This is 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's performance is based on objective measurements and results from standardized non-clinical engineering tests (ISO 7176 series) and biocompatibility tests (ISO 10993 series). For example, a wheelchair either passes the static stability test at a certain angle or it doesn't; this is a measured outcome against a defined specification, not an expert opinion.

8. The sample size for the training set

• This is not applicable. This device is a physical product and does not involve AI/machine learning models that require training sets.

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

• This is not applicable. As it's not an AI device, there is no training set or associated ground truth establishment process.

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