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510(k) Data Aggregation
(322 days)
The Novaerus NV 1050 is intended as a room recirculating air cleaner. The system is used for filtering out and inactivating airborne particles from the air for medical purposes.
The Novaerus NV1050 (NV1050) is a free-standing cabinet of a size that can be maneuvered into position by a single person. The NV1050 is powered from an AC wall outlet. The NV1050 circulates the room air through its cabinet. The air is drawn in through the front of the cabinet, passes through a pre-filter then a Dielectric Barrier Discharge Plasma generator ("plasma generator") stage, and a further two filters (HEPA, Carbon) The cleaned air is exhausted out of the top panel of the cabinet. The device has simple controls: On/Off and fan speed setting from 1 to 5. There is a button to initiate a filter blockage test to check and inform the user if the filters are getting close to requiring changing. The only routine maintenance is a calendar-based filter change schedule indicated in the User Manual; the indicator light on the front panel acts as a reminder that the filters will soon need attention. The airflow path through the NV1050 is: - A general pre- filter to remove particles from the input air flow. . - A bank of three (3) plasma generators, each Plasma Generator consists of ● two (2) plasma Coils. Micro-Organisms, including virus and bacteria, are inactivated by the plasma generator. This occurs through damage by plasma constituents (ions, electrons, reactive oxidizing species, ultraviolet radiation, high electric fields) - A HEPA (High-efficiency Particulate Air) filter to trap the resulting virus/bacteria particulates. - . An activated carbon filter to trap any ozone in the airstream before it is output to the environment.
The provided text describes the Novaerus NV1050 medical recirculating air cleaner and its substantial equivalence to a predicate device. It includes information on non-clinical testing to demonstrate performance against acceptance criteria.
Here's the breakdown of the requested information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Test name/Methodology/Standard name | Purpose | Acceptance Criteria | Result |
|---|---|---|---|
| IEC60601-1:2005/A1;2012 | Device electrical safety | Pass the requirements of the consensus standard | Pass |
| IEC60601-1-2:2014 | Device Electromagnetic Compatibility | Pass the requirements of the consensus standard | Pass |
| Ozone emissions | Confirm ozone emissions are below the maximum permitted levels <0.050 ppm | Ozone emitted to be <0.050 ppm | Pass in normal operating conditions and single fault conditions including operating with blocked and past end of life filters |
| Inactivation of Micro-organisms | To demonstrate that the plasma technology alone can produce a 4 log reduction in viable micro-organisms | The plasma generator alone produces a 4 log reduction in a specified micro-organism | A single plasma generator of the type embodied in the NV1050 produced a 4 log reduction in MS2 Bacteriophage in 5 hours when operating in a sealed 580ft3 (16.4m3) room |
| Filtration of particles | To demonstrate that the filter banks alone can produce a 4 log reduction in particles | The device produces a 4 log reduction in the concentration of µm sized polystyrene microspheres | The device produced a 4 log reduction in the concentration of 0.5 to 2.0 µm sized polystyrene microspheres in a sealed 580ft3 (16.4m3) room in 10 minutes |
| Combined Operation | To demonstrate the performance of the NV1050 at maximum speed to inactivate and filter out specified micro-organisms | To produce a 4 log reduction in the specified micro-organisms | NV1050 running at maximum speed in a 580ft3 (16.4m3) sealed room: • Bacillus Globigii Endospores: A 4 log reduction produced in 15 minutes. Prolonged operation over 24 hours to confirm that the reduction in the micro-organisms was maintained and no viable micro-organisms were recycled back into the ambient air. • MS2 Bacteriophage: A 4 log reduction produced in 15 minutes. |
2. Sample size used for the test set and the data provenance
- Sample Size for Test Set: The sample size for the "Inactivation of Micro-organisms", "Filtration of particles", and "Combined Operation" tests involved a single device (Novaerus NV1050) operating in a sealed 580ft3 (16.4m3) room. For the electrical safety and EMC tests, the sample size is not explicitly stated but implies testing of the device itself.
- Data Provenance: The document does not specify the country of origin of the data or whether the studies were retrospective or prospective. It only states that "The following performance data has been provided to demonstrate that the subject device meets the acceptance criteria of the standards listed below." The tests appear to be laboratory-based performance evaluations rather than clinical studies on patient populations.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The provided text describes performance testing of an air cleaning device; it does not involve establishing ground truth from expert interpretation of medical images or data. Therefore, this question is not applicable in this context. The ground truth for these tests would be the measured reduction in microorganisms or particles, or compliance with electrical and EMC standards, based on established scientific methods and instrumentation, not expert consensus.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This question is not applicable as the described testing methodology is for device performance (reduction of microorganisms, filtration, electrical safety, EMC) rather than the interpretation of data where adjudication among readers would be necessary.
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
An MRMC study is relevant for AI-assisted diagnostic devices involving human readers. The Novaerus NV1050 is an air cleaning device, and its performance evaluation does not involve human readers interpreting data. Therefore, an MRMC comparative effectiveness study was not done, and this question is not applicable.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This question is framed for AI algorithms. For this device, the "standalone" performance refers to the device's ability to reduce microorganisms and filter particles on its own, without human intervention in its air purification function. The tests for "Inactivation of Micro-organisms," "Filtration of particles," and "Combined Operation" demonstrate the device's standalone performance in a controlled environment.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The ground truth for the performance tests described involves:
- Quantitative measurement of reduction: For microorganism inactivation, the ground truth is the measured log reduction of MS2 Bacteriophage and Bacillus Globigii Endospores. For particle filtration, it's the measured log reduction of polystyrene microspheres.
- Compliance with standards: For electrical safety and electromagnetic compatibility, the ground truth is whether the device meets the specified requirements of IEC 60601-1 and IEC 60601-1-2.
- Quantitative measurement of emissions: For ozone emissions, the ground truth is the measured concentration of ozone.
These are objective, empirical measurements based on scientific methodologies rather than expert consensus, pathology, or outcomes data typically associated with diagnostic medical devices.
8. The sample size for the training set
The provided text only discusses non-clinical performance testing of the final device and does not mention any "training set" for AI/machine learning. This device is an air cleaner, not an AI-driven diagnostic or therapeutic system that would typically require training data. Therefore, this question is not applicable.
9. How the ground truth for the training set was established
As there is no mention of a training set for an AI/machine learning model, this question is not applicable.
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