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The Chad Therapeutics Evolution Model OM-900M is intended for prescription use only, to be used as part of a portable oxygen delivery system for patients that require supplemental oxygen up to 6 liters per minute, in their home and for ambulatory use.

The Inovo Evolution OM-900M is a microprocessor-controlled device, which is a combination of a oxygen pressure regulator and a oxygen conserver, designed for use with ambulatory oxygen systems. The built in oxygen regulator reduces the oxygen pressure from the oxygen cylinder to ensure proper operation of the oxygen conserving device. The low pressure oxygen enters the conserver portion of the device where the breath detection circuitry and inhalation sensors control the low pressure oxygen to deliver a precise amount of supplemental oxygen at a specific point in the breathing cycle. It delivers boluses of oxygen that is equivalent to 1 to 6 liters per minute depending on the user setting. The OM-900M is also able to detect motion via a 3 axis accelerometer. If motion is detected the software will automatically increase the oxygen delivery(active mode) to the patient. After motion has ceased, the software will then revert to the original rest setting(rest mode). The motion technology is taken from a previously cleared device Chad Sage Model TD-100 - K033364.

The Inovo Evolution OM-900M is an oxygen conserver. The provided text describes the device, its intended use, and a comparison to predicate devices, focusing on the addition of a motion detection feature.

Here's an analysis to extract the requested information regarding acceptance criteria and the study proving the device meets them:

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

The provided 510(k) summary (K113111) for the Inovo Evolution OM-900M does not explicitly state a table of quantifiable acceptance criteria with corresponding device performance metrics for the overall device or its new motion detection feature. Instead, it relies on demonstrating substantial equivalence to predicate devices through verification and validation activities.

However, based on the text, the implicit acceptance criteria are that the modifications (motion detection software and hardware) do not introduce new safety and effectiveness issues and that the device functions as intended, similar to the predicate devices.

The "reported device performance" is broadly stated as passing all tests outlined in the validation protocols. Specific quantitative performance targets for the motion detection feature itself (e.g., accuracy of motion detection, response time to motion, or how much oxygen delivery increases) are not detailed in this summary.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify a separate "test set" in the context of and AI/algorithm-focused study with a defined sample size of patients or images. The verification and validation activities (PV-192 and PV-193) are described as testing the software and hardware of the device. This implies engineering or laboratory testing rather than a clinical trial with human subjects.

Therefore, information on sample size for a "test set" and data provenance (country of origin, retrospective/prospective) related to AI/algorithm performance is not applicable or provided in this 510(k) summary. These types of details are typically found in clinical study reports, which are not included here.

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 as the document does not describe a study involving expert-established ground truth for a test set (e.g., for image interpretation or disease diagnosis). The verification and validation activities are for the device's functional performance, not for an AI algorithm making diagnostic interpretations.

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

This information is also not applicable as there is no mention of a test set requiring adjudication of findings, which is typical for clinical studies involving multiple reviewers or diagnostic outputs.

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

No, an MRMC comparative effectiveness study was not done or described in this 510(k) summary. This type of study is relevant for AI systems that assist human readers in tasks like medical image interpretation. The Inovo Evolution OM-900M is an oxygen conserver with a motion detection feature, not an AI-powered diagnostic tool in that sense.

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

The device's motion detection feature can be considered a standalone algorithmic component that senses motion and automatically adjusts oxygen delivery without direct human intervention once activated. The "Non Clinical Verification" section describes that the software for the motion detection algorithm underwent full Software Verification and Validation (PV-192), and the hardware was tested via Product Validation (PV-193).

However, the nature of these tests is focused on the correct functioning of the motion detection system (e.g., does it detect motion, does it switch to active mode, does it revert to rest mode correctly) rather than a comparative performance against a "ground truth" of human activity, or direct clinical outcomes. The document does not provide specifics on the metrics used to assess this "standalone" performance beyond stating that it "passed all tests."

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

For the verification and validation of the motion detection feature, the "ground truth" would likely be based on engineering specifications and predefined performance thresholds for the accelerometer and associated software.

• For software verification (PV-192), the ground truth for tests would be the expected software behavior based on the Software Requirements Specification (SP-210) and Software Design Description (SP-209). For example, if a specific motion is simulated, the device should switch to active mode.
• For hardware validation (PV-193), the ground truth would involve confirming that the accelerometer correctly senses motion within specified parameters and that the additional button functions as intended.

It is not based on expert consensus, pathology, or clinical outcomes in the traditional sense of a diagnostic AI system study.

8. The sample size for the training set

This information is not applicable. The motion detection functionality appears to be based on an algorithm that processes accelerometer data rather than a machine learning model that requires a "training set" of data to learn from. The description suggests a rule-based or threshold-based system rather than a deep learning approach.

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

This information is not applicable as there is no mention of a training set for a machine learning algorithm.

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The Chad Therapeutics Evolution Model OM-900 is intended for prescription use only, to be used as part of a portable oxygen delivery system for patients that require supplemental oxygen up to 7 liters per minute, in their home and for ambulatory use

The Inovo Evolution is a microprocessor-controlled device, which is a combination of a oxygen pressure regulator and a oxygen conserver, designed for use with ambulatory oxygen systems. The built in oxygen regulator reduces the oxygen pressure from the oxygen cylinder to ensure proper operation of the oxygen conserving device. The low pressure oxygen enters the conserver portion of the device where the breath detection circuitry and inhalation sensors convert the low pressure oxygen to deliver a precise amount of supplemental oxygen at a specific point in the breathing cycle. It delivers boluses of oxygen that is equivalent to 1 to 7 liters per minute depending on the flow rate setting

Here's an analysis of the provided text regarding the acceptance criteria and study information for the Inovo Evolution OM-900 Series:

Disclaimer: The provided text is a 510(k) summary from 2010. It focuses on demonstrating substantial equivalence to a predicate device, which means it might not contain the detailed, quantitative acceptance criteria and study results typically found in full clinical study reports or newer FDA submissions. Much of the information requested (e.g., sample sizes for training/test sets, expert qualifications, specific metrics for acceptance criteria) is not present in the provided document.

Acceptance Criteria and Reported Device Performance

The 510(k) summary for the Inovo Evolution OM-900 Series is primarily a submission for substantial equivalence. It does not explicitly state quantitative acceptance criteria in a table format with corresponding performance results in the way a performance study might. Instead, it relies on demonstrating that its design, function, and features are comparable to the predicate device (Chad Therapeutic Lotus Models OM-700 & OM-700S) and that testing confirms it performs as intended and meets the same "performance criteria" as the predicate.

The key acceptance criteria, as implied by the document, revolve around:

• Same Intended Use: The device must serve the same purpose for the same patient population.
• Basic Modes and Settings: It must offer comparable operational modes and settings.
• Similar Materials: The materials used should be equivalent.
• Equivalent Oxygen Delivery Method: The fundamental way it delivers oxygen should be the same.
• Performance (General): Testing must demonstrate it meets performance criteria and functions as intended, implying that its oxygen delivery characteristics (bolus size, equivalence to L/min, breath detection) are comparable to the predicate.

Since no specific quantitative metrics or a comparative table are provided in the document, I cannot populate a table with "acceptance criteria" vs. "reported performance" with specific numbers. The document states a general conclusion:

"together with the results of testing demonstrates the device to be substantially equivalent to the predicate device in terms of meeting performances criteria and functioning as intended."

This indicates that internal testing was conducted to ensure the device performs similarly to the predicate, particularly regarding breath detection (even though the circuitry is new) and bolus sizes. The bolus sizes are explicitly mentioned as "the same with the exception of one additional setting No. 7."

Detailed Study Information (Based on Available Text)

1. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

   • Not provided. The document states "results of testing," but does not specify the type of testing (e.g., in vitro, animal, human clinical), sample size, or data provenance. Given the nature of a 510(k) for an oxygen conserver, it's likely initial testing focused on engineering and performance verification in a lab setting, possibly with some human-factors or usability testing, rather than a large clinical trial with patient data.

2. 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)

   • Not applicable/Not provided. This type of information is usually relevant for studies involving image interpretation or diagnostic accuracy where expert consensus is needed to establish ground truth. For an oxygen conserver, ground truth would likely be established through objective measurements of oxygen delivery, breath detection accuracy, and functionality, rather than expert interpretation.

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

   • Not applicable/Not provided. Adjudication methods are typically used in studies where multiple human readers interpret data (e.g., medical images) and their discrepancies need to be resolved to establish ground truth. This is not the type of study described or implied for this device.

4. 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

   • No. An MRMC comparative effectiveness study is not mentioned and is not relevant for an oxygen conserver device, which is a therapeutic device, not an AI-assisted diagnostic tool for human readers.

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

   • Not applicable/Not provided in this context. While the device is microprocessor-controlled and has "breath detection circuitry," it's a medical device delivering oxygen, not an AI algorithm generating a diagnosis or prediction without human interaction. Performance testing would have evaluated the device's standalone operation and its ability to deliver oxygen accurately based on detected breaths. However, the term "standalone" in the context of AI performance metrics (algorithm only) is not relevant here.

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

   • Objective Measurements/Engineering Specifications. For an oxygen conserver, ground truth would be established through objective measurements based on engineering specifications and physiological principles. This would include accurately measuring:
     • Oxygen flow rates and bolus sizes
     • Accuracy of breath detection
     • Battery life
     • Pressure regulation
     • Safety parameters (e.g., leaks, pressure limits)
   • The document implies that these measurements were compared against the predicate device's known performance characteristics and relevant standards.

7. The sample size for the training set

   • Not applicable/Not provided. This device is hardware-based with microprocessor control, not a machine learning or AI algorithm that requires a "training set" in the conventional sense. The "training" for such a device involves design, engineering, and iterative testing/refinement of the hardware and embedded software.

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

   • Not applicable/Not provided. As above, the concept of a "training set" and its "ground truth" is not directly applicable to this type of device development process. Ground truth for the underlying principles (e.g., desired oxygen bolus sizes, breath detection sensitivity) would be established by medical standards, physiological requirements, and the performance characteristics of the predicate device.

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