Search Results

The Oxygen Concentrators are indicated for the delivery of supplemental oxygen in the home or medical institutions. The device is not intended for life support nor does it provide any patient monitoring capabilities.

The Merits Health Products Oxygen Concentrators are prescription devices designed to provide an inexpensive supply of supplemental oxygen in a home or institution without a continuous source of purified oxygen. They are not life-supporting nor life-sustaining devices. The devices operate through the use of molecular sieve material that binds with the water and nitrogen in filtered room air to leave a gas that is approximately 93% oxygen when delivered to the patient. The compressor creates a vacuum to draw room air into a holding tank. At the same time, downstream of the compressor, the air from the previous cycle is pressurized into one of the two aluminum welded molecular sieve tanks. As the oxygen is forced out of the end of the tank, it enters a "T" fitting that directs most of the gas to flush the nitrogen out of the second molecular sieve tank into the ambient air. The remaining oxygen is delivered to the patient. On the next cycle, the air is directed into the second molecular sieve tank with the oxygen generated flushing the first tank and continuing the supply to the patient. This repetitive cycle generates the oxygen necessary to flush and prepare the saturated sieve tank while supplying the patient with a continuous flow of high concentration oxygen. Options will include an Oxygen alarm and a pediatric flowmeter

The provided text is a 510(k) summary for the Merits Health Products Oxygen Concentrator. It describes the device and claims substantial equivalence to a predicate device. However, it does not contain details about specific acceptance criteria, a study proving the device meets those criteria, or information related to AI/algorithm performance analysis.

Based on the provided text, here's what can be extracted:

1. A table of acceptance criteria and the reported device performance
   The document states: "The results of the testing confirm that the device meets specifications and is substantially equivalent to the predicate device." However, it does not provide a table of the specific specifications (acceptance criteria) or the detailed performance results. It generally claims equivalence to the predicate device (K011884).

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 present in the provided text.

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 present in the provided text. The device is an oxygen concentrator, not an imaging or diagnostic AI device that would typically involve expert ground truth for a test set in the same way.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
   This information is not present in the provided text. It is not relevant for this type of device 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 present in the provided text. This is a medical device (oxygen concentrator), not an AI-assisted diagnostic tool, so an MRMC study with human readers and AI assistance would not be applicable.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
   This information is not present in the provided text. This is an oxygen concentrator, not an algorithm, so "standalone algorithm performance" is not applicable.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
   This information is not present in the provided text. For an oxygen concentrator, "ground truth" would likely relate to objective measurements of oxygen concentration, flow rates, and safety parameters, rather than expert consensus on diagnostic images or pathology.

8. The sample size for the training set
   This information is not present in the provided text. This device is not an AI/ML algorithm that requires a training set in the conventional sense.

9. How the ground truth for the training set was established
   This information is not present in the provided text, as it's not applicable to this type of device.

Ask a specific question about this device