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My product is constructed of the same materials, as that of all the lift chair manufacturers I have provided. The chairs consist of oak wood, foam and fabric. The steel frame is constructed of 1"x 1", 16 gauge steel and also 1"x 2" 14 gauge steel.

This document, K961663, is a 510(k) premarket notification for a lift chair. It is a submission for a medical device and describes its equivalence to existing predicate devices. However, it does not contain the type of structured data and study information typically found in submissions for AI/ML-driven medical devices that involve performance metrics like sensitivity, specificity, or AUC.

Therefore, I cannot extract the information requested in the prompt, such as acceptance criteria tables, sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, or standalone performance.

The document primarily focuses on establishing substantial equivalence by stating:

• The use of UL listed and CSA approved motors and switches (same as predators).
• The lift chair market's long existence, implying established safety profiles.
• The use of similar materials (oak wood, foam, fabric, steel frame) as predicate devices.
• The same weight capacity (300 lbs) as predicate devices.
• Similar frame base width for stability as predicate devices.

In summary, this document is a comparison to predicate devices based on design and materials, not a performance study for a novel AI/ML algorithm or system.

If you have a document related to an AI/ML medical device submission, please provide that, and I will do my best to extract the requested information.

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