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The Portable Oxygen Concentrator (Model: P2-E7, P2-E) is intended to provide supplemental oxygen in a home, institutional, or travel environment.

Portable Oxygen Concentrator (Model: P2-E7, P2-E) is a portable oxygen generator that is intended to release oxygen for respiratory by means of physical means (a molecular sieve). It supplies a pulsed high concentration of oxygen and is used with a nasal cannula to channel oxygen from the concentrator to the patient. The Portable Oxygen Concentrator is small, portable and may be used in home, institutional, or travel environment.

The portable oxygen concentrator consists of two parts: an oxygen concentrator and accessories. The oxygen concentrator is composed of compressor, battery, solenoid valve, molecular sieve, circuit control system, heat dissipation system, and a flow control device. Accessories include power adapters.

Model difference: The only different between model P2-E7 and P2-E is that P2-E7 has biggest output oxygen flow of 1.4L/min (at 7 gears) and P2-E has biggest output oxygen flow of 1.0L/min (at 5 gears).

The provided document is a 510(k) Summary for a Portable Oxygen Concentrator. It describes the device, its intended use, and a comparison to a predicate device to establish substantial equivalence for regulatory clearance. It does not present information about a study that assesses the device's performance against clinical acceptance criteria using human subjects or an AI algorithm.

Therefore, I cannot provide the requested information regarding:

• A table of acceptance criteria and reported device performance (in a clinical context).
• Sample size used for a test set or data provenance related to clinical performance.
• Number of experts or their qualifications for establishing ground truth for a clinical test set.
• Adjudication method for a clinical test set.
• MRMC comparative effectiveness study or related effect sizes.
• Standalone (algorithm only) performance.
• Type of ground truth used (expert consensus, pathology, outcomes data, etc.) for clinical evaluation.
• Sample size for a training set (as no AI algorithm requiring a training set is discussed).
• How ground truth for a training set was established.

The document focuses on non-clinical testing and engineering standards to demonstrate safety and effectiveness, and substantial equivalence to a predicate device, not clinical performance against acceptance criteria in a human study, nor does it involve an AI component.

The relevant information from the document related to testing and "acceptance" is as follows:

Acceptance Criteria (Implied by Standards and Comparison to Predicate):

While not explicitly stated as "acceptance criteria" in a clinical performance sense, the document demonstrates the device meets various safety, performance, and compatibility standards. The "reported device performance" in this context refers to the device's adherence to these standards and its characteristics in comparison to the predicate.

Study Proving Device Meets Criteria:

The "study" in this context refers to the non-clinical testing and validation performed to demonstrate substantial equivalence and adherence to recognized standards.

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

2. Sample sized used for the test set and the data provenance: Not applicable in the context of human clinical data for this submission. The "test sets" refer to the specific units of the device models (P2-E7, P2-E) subjected to various engineering and functional tests. The data provenance is from Qingdao Kingon Medical Science and Technology Co., Ltd. (China) through bench testing. The document refers to "non-clinical tests performed." The testing is retrospective in the sense that the results were submitted for regulatory review after completion.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth, in this context, is established by adherence to internationally recognized engineering and medical device standards (e.g., ISO, IEC, AAMI ANSI) and direct measurement of device characteristics. The expertise would lie in the engineers and testing personnel who conducted these standard tests.

4. Adjudication method: Not applicable. Standard technical testing and comparison against predicate.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done: No. This type of study is for evaluating human performance, often with or without AI assistance, in diagnostic tasks. This device is a portable oxygen concentrator, not an imaging or diagnostic AI device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The "software" in this device controls hardware functions (e.g., alarms, breath detection, display) and is deeply embedded, not a standalone AI algorithm for interpretation or diagnosis.

7. The type of ground truth used: For hardware performance, the ground truth is defined by the specifications in the relevant industry standards (e.g., oxygen concentration, pressure, noise levels) and the functional requirements of the device. For software, the "ground truth" is adherence to software development life cycle processes (IEC 62304) and correct execution of defined functions without critical errors.

8. The sample size for the training set: Not applicable. This device does not use an AI algorithm that requires a training set in the typical machine learning sense. The software is embedded control software.

9. How the ground truth for the training set was established: Not applicable. See point 8.

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