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The YJ-K1/K2 Manual Wheelchair is to provide mobility to persons limited to a sitting position.

The YJ- K1,K2 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.

The provided document pertains to a 510(k) premarket notification for a manual wheelchair (YJ-K1/K2 Wheelchair) and does not describe acceptance criteria or a study related to an AI/ML-driven device. The document primarily focuses on demonstrating substantial equivalence to a predicate manual wheelchair through non-clinical performance testing and biocompatibility testing.

Therefore, the requested information regarding acceptance criteria, study details for AI/ML performance, sample sizes, expert involvement, adjudication methods, MRMC studies, standalone performance, ground truth, and training sets is not available within this document.

The document states:

• "No clinical study is included in this submission." (Page 8)
• The tests conducted are non-clinical, focusing on mechanical performance and biocompatibility to standards like ISO 7176 series and ISO 10993 series. (Page 8)
• The device is a "mechanical wheelchair" (Page 5).

Since the request is specifically for a device that would require such studies (e.g., an AI/ML diagnostic device), and this document describes a manual wheelchair, it is not possible to extract the requested information.

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The YJ-011S Manual Wheelchair is to provide mobility to persons limited to a sitting position.

The YJ-011S series 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.

The provided text describes a 510(k) premarket notification for a reclining wheelchair, which is a Class I device. As such, the submission focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance and biocompatibility testing, rather than a clinical study or AI/software validation. Therefore, many of the requested elements regarding acceptance criteria for AI performance, clinical study details, expert review, effect size, and training/test set specifics are not applicable or not present in this type of regulatory submission.

Applicable Information from the Submission:

This submission for the Zhenjiang Assure Medical Equipment Co., Ltd. Reclining Wheelchair (K232198) primarily relies on demonstrating compliance with recognized performance standards for mechanical wheelchairs and biocompatibility testing. The "acceptance criteria" are implied by the successful execution and results of these tests, showing the device meets the safety and performance benchmarks established by the standards and is comparable to the predicate device.

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

The submission does not present a formal "acceptance criteria" table with specific quantitative thresholds that would be typical for an AI/software device. Instead, acceptance is demonstrated by compliance with international standards for wheelchairs and biocompatibility. The "reported device performance" is that the device complied with these standards.

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 applicable. The evaluations were non-clinical performance and biocompatibility tests of the physical device, not an assessment of software or AI performance on a data set. Therefore, there is no "test set" in the context of data or images, nor data provenance.

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. There was no test set requiring expert ground truth establishment for this type of medical device submission.

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

This information is not applicable. There was no test set requiring adjudication in this type of submission.

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. This device is a mechanical wheelchair, not an AI-assisted diagnostic or interpretative device. Therefore, no MRMC study or assessment of human reader improvement with AI assistance was performed.

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

This information is not applicable. This device is a mechanical wheelchair and does not involve an algorithm.

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

This information is not applicable in the context of "ground truth" for AI/software. The "ground truth" for this device's performance is defined by the established criteria and methods within the referenced ISO standards for mechanical wheelchairs and biocompatibility.

8. The sample size for the training set

This information is not applicable. This device is a mechanical wheelchair and does not involve AI or machine learning that would require a training set.

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

This information is not applicable. This device is a mechanical wheelchair and does not involve AI or machine learning that would require a training set or its associated ground truth establishment.

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The YJ-010B Manual Wheelchair is to provide mobility to persons limited to a sitting position.

The YJ-010B series 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 footplates 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.

The provided document is a 510(k) premarket notification for a Bariatric Heavy Duty Wheelchair. It does not describe an AI medical device or a study involving AI assistance or human readers. Therefore, I cannot extract information related to acceptance criteria and study proving a device meets those criteria for an AI-powered device, as the document pertains to a mechanical wheelchair.

The document discusses:

• Acceptance criteria (implicitly): The device (a manual wheelchair) needs to demonstrate substantial equivalence to a predicate device, primarily through non-clinical performance testing and biocompatibility assessments, adhering to various ISO standards.
• Device performance: The document lists various specifications of the proposed wheelchair (e.g., dimensions, weight capacity, stability angles, brake effectiveness) and states that these comply with relevant ISO standards.
• Ground Truth: For a mechanical device like a wheelchair, "ground truth" would relate to its physical properties and performance metrics as measured according to established engineering and safety standards (e.g., ISO 7176 series).
• Sample Size: Not applicable in the context of an AI test set. This refers to physical samples of the wheelchair models being tested.
• Experts/Adjudication/MRMC/Standalone: These concepts are not applicable to the evaluation of a mechanical wheelchair. There is no AI algorithm being evaluated.
• There is no clinical study included in this submission.

To answer your request, here's a blank template for an AI medical device study, illustrating the elements you've asked for, as this document does not contain the necessary information.

Acceptance Criteria and Study for an AI Medical Device

Study Description:
(This section would be filled if the document were about an AI device. As it is not, this remains a template.)

1. Table of Acceptance Criteria and Reported Device Performance

Note: The above table is a placeholder for a hypothetical AI device study and cannot be populated from the provided document, which describes a mechanical wheelchair.

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

• Test Set Sample Size: [Number of cases/patients/images]
• Data Provenance: [e.g., Retrospective or Prospective; Country of origin (e.g., Multi-site from US, Europe, Asia)]

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

• Number of Experts: [ e.g., 3]
• Qualifications of Experts: [e.g., Board-certified Radiologists with >10 years of experience in [specific domain, e.g., chest imaging, mammography]; Certified Pathologists with >5 years of experience]

4. Adjudication Method for the Test Set

• Adjudication Method: [e.g., 2+1 (two initial readers, third independent reader for discordance); 3+1 (three initial readers, fourth independent reader for discordance if majority not reached); Consensus meeting; None (if single reader ground truth)]

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, What Was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance?

• MRMC Study Conducted?: [Yes/No]
• Effect Size (e.g., improvement in AUC or F-measure for human readers with AI assistance vs. without AI): [e.g., Human readers' AUC improved from X to Y (an absolute increase of Z); F-measure increased by Z%]

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

• Standalone Performance Study Conducted?: [Yes/No]
• Key Performance Metrics (if Yes): [e.g., Sensitivity: X%, Specificity: Y%, AUC: Z]

7. The Type of Ground Truth Used

• Type of Ground Truth: [e.g., Expert consensus (radiologist readings); Pathological diagnosis (biopsy/histology); Clinical outcomes data (e.g., hospital discharge codes, follow-up imaging); Longitudinal follow-up data]

8. The Sample Size for the Training Set

• Training Set Sample Size: [Number of cases/patients/images]

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

• Ground Truth Establishment for Training Set: [e.g., Clinical reports by attending physicians; Single expert review; Automated label extraction; A subset might be expert-reviewed, while the majority are from routine clinical practice.]

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