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The O2 Concepts Oxlife Independence is indicated on a prescription basis for the administration of supplemental oxygen. It is not intended for life support, nor does it provide any patient monitoring capabilities.

The Oxlife Independence is a portable oxygen concentrator that enables patients requiring supplemental oxygen to be treated in a home environment, in an institutional environment or in a vehicle/mobile environment. The Oxlife Independence utilizes O2 Concepts' Dynamic Network Analysis (DNA) technology to provide equipment performance, location and usage data to O2 Concepts and its customers via cellular and GPS connection. The device delivers 87%-95% pure oxygen to a patient through a standard single lumen nasal cannula. The Independence detects a patient breath and delivers a bolus of oxygen during the inhalation period in pulse mode or delivers a continuous flow of oxygen in continuous mode.

This document describes the O2 Concepts Oxlife Independence Model 301-0001, a portable oxygen concentrator, and its 510(k) submission for FDA clearance. The information provided is primarily focused on demonstrating substantial equivalence to a predicate device, rather than an AI/ML software as a medical device (SaMD). As such, the request for specific AI/ML-related acceptance criteria and study details (like MRMC studies, ground truth establishment for training sets, or sample sizes for test/training sets in the context of AI model performance) are not directly applicable or available in the provided text.

The document focuses on engineering and usability testing for a hardware device, not the performance claims of an AI algorithm.

However, I can extract and present the available acceptance criteria and performance data for this hardware device based on the provided text, while explicitly stating where requested information related to AI/ML is not applicable or not found.

Here's an attempt to structure the information based on your request, noting the limitations of the provided document in the context of AI/ML performance studies:

Acceptance Criteria and Device Performance for O2 Concepts Oxlife Independence Model 301-0001

This device is a hardware portable oxygen concentrator, and its clearance is based on demonstrating substantial equivalence to a predicate device, primarily through engineering performance testing and usability studies. It is not an AI/ML algorithm or SaMD. Therefore, many of the requested criteria related to AI/ML performance (e.g., AUC, sensitivity/specificity, MRMC studies, training set details for an AI model) are not relevant or described in this submission.

1. Table of Acceptance Criteria and Reported Device Performance

The document describes performance in terms of meeting various standards and demonstrating equivalence to the predicate. The "acceptance criteria" here are largely implied by compliance with recognized standards and successful verification/validation testing.

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

• Test Set Description: The "test set" in this context refers to the physical devices and materials subjected to engineering and usability testing, not a dataset for an AI model.
• Sample Size:
  • Usability Testing: 10 users were involved.
  • Other Testing (Biocompatibility, Electrical Safety, V&V): The document does not specify the exact number of physical units tested for each specific engineering test. It refers to "testing of prototype devices" and "testing of production units."
• Data Provenance: The testing was conducted internally by O2 Concepts LLC (or through contracted labs, as implied by compliance statements). No information on country of origin of data or specific retrospective/prospective data collection is relevant or provided, as this is hardware testing for regulatory compliance.

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

• Not Applicable in the AI/ML context. This device is a hardware product. Ground truth for its performance is established through physical measurements, compliance with engineering standards, and usability observations, not expert consensus on medical images or patient outcomes data as would be the case for an AI diagnostic tool.
• For usability: "10 users" were involved in the usability study, implying they represent the "intended user population." Their specific qualifications are not detailed beyond being representative users.

4. Adjudication Method for the Test Set

• Not Applicable in the AI/ML context. Adjudication methods (2+1, 3+1) refer to procedures for resolving disagreements among multiple human readers when establishing ground truth for AI model performance. As this is a hardware device, such methods are not relevant.
• For engineering tests: Pass/fail criteria against established standards (e.g., IEC 60601-1) or design specifications serve as the "adjudication."

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No. An MRMC study is a clinical study design used to evaluate the performance of diagnostic tools (often AI/ML) by comparing multiple readers' interpretations of cases with and without AI assistance. This is a hardware oxygen concentrator, not a diagnostic AI tool, so this type of study was not performed or applicable.

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

• Not Applicable. This is not an AI algorithm. Its performance is inherent to its mechanical and electronic design. The closest equivalent would be the various engineering performance tests (e.g., oxygen concentration, flow rate accuracy, electrical safety) that demonstrate the device's functional integrity.

7. The Type of Ground Truth Used

• For device performance: The "ground truth" for this device's performance is established by:
  • Physical Measurements: Direct measurements of oxygen concentration, flow rates, acoustic noise, battery duration, etc., using calibrated equipment.
  • Compliance with Recognized Standards: Meeting the requirements of international and national standards for medical electrical equipment (e.g., ISO 80601-2-69, IEC 60601 series, ISO 10993 for biocompatibility).
  • User Observations: For usability, "successful operation" by intended users per the study protocol.

8. The Sample Size for the Training Set

• Not Applicable. This is a hardware medical device, not an AI/ML algorithm. There is no "training set" in the context of machine learning.

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

• Not Applicable. As there is no AI/ML training set, this question is not relevant.

Summary of Device Nature:
The O2 Concepts Oxlife Independence Model 301-0001 is a portable oxygen concentrator, a Class II hardware medical device. Its 510(k) clearance relied on demonstrating substantial equivalence to a predicate device, primarily evidenced through engineering performance tests (e.g., oxygen purity, flow rates, electrical safety), biocompatibility testing, and a usability study. The concept of an AI model, training data, test data for AI, or AI-specific performance metrics are not applicable to this submission.

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