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510(k) Data Aggregation
(24 days)
The various models of Inovel Type N95 Healthcare Particulate Respirators and Surgical Masks meet CDC Guidelines for TB Exposure Control within healthcare facilities. These devices are also intended to be worn by healthcare personnel during surgical procedures to protect both the patient and healthcare personnel from the transfer of microorganisms, body fluids and particulate material.
The Inovel type N95 Healthcare Particulate Respirators and Surgical Masks are constructed from an extruded plastic mesh used in the outer cover and a nonwoven spunbond used in the inner and outer cover. The polypropylene melt blown filter media is layered between the inner and outer cover. The head strap is made of a non-latex rubber stapled to the mask. The inside nosepiece is a closed cell foam.
This looks like a 510(k) premarket notification for N95 Particulate Respirators and Surgical Masks. The document provides acceptance criteria and performance data for these masks across several characteristics. Since this is a submission for a physical medical device (respirator/mask), the typical "study" that would prove the device meets acceptance criteria involves physical and material property testing, rather than a clinical trial or algorithm performance study.
Here's the breakdown of the requested information based on the provided text, adapted for the nature of this physical device submission:
1. Table of Acceptance Criteria and Reported Device Performance
| Performance Characteristic | Test Method | Acceptance Criteria | Reported Device Performance (MFRN95 Models) |
|---|---|---|---|
| Fluid Resistance | ASTM 1862 - 00a | 32 of 32 pass (implies resisting penetration by synthetic blood) | Models MFRN95-S, MFRN95-XS, MFRN95-ML, MFRN95-A, MFRN95-MLZ: 32 of 32 pass; Model MFRN95-SZ: 31 of 32 pass (Meets acceptance for most models, one model has one failure) |
| Flammability Class | 16 CFR 1610 | Flame spread must be within upper and lower limits / No flame spread on 10 of 10 samples, meets Class I | No flame spread on 10 of 10 samples, meets Class I |
| Filter Efficiency (%) | NIOSH, 42 CFR Part 84 | > 95% Efficient | Average 99.46% efficient of 40 samples |
| Breathing Resistance | NIOSH, 42 CFR Part 84 | ≤ 35.0 mm H2O @ 85 lpm (inhalation resistance); ≤ 25.0 mm H2O @ 85 lpm (exhalation resistance, implied by NIOSH N95 standard) | Average 12.5 mm H2O @ 85 lpm of 18 samples (inhalation, implying it's well below the limit) |
2. Sample Size Used for the Test Set and Data Provenance
- Fluid Resistance (ASTM 1862 - 00a): 32 samples per model tested.
- Flammability (16 CFR 1610): 10 samples.
- Filter Efficiency (NIOSH, 42 CFR Part 84): 40 samples.
- Breathing Resistance (NIOSH, 42 CFR Part 84): 18 samples.
The data provenance is not explicitly stated in terms of country of origin, but the tests refer to established US standards (ASTM, NIOSH, CFR) and were conducted by "Nelson Laboratories" for Bacterial Filtration Efficiency (though the table uses NIOSH for Filter Efficiency). Given the submission is to the FDA, it is presumed to be for the US market, and tests are likely conducted in US-based accredited laboratories or to US standards. All data appears to be prospective results from laboratory testing conducted on the device models for this submission.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts
This section is not applicable in the context of this device. The "ground truth" for N95 respirators and surgical masks is established by standardized, objective physical and performance test methods (e.g., measuring filter efficiency with a particle counter, measuring flame spread with a direct flame application) defined by regulatory bodies and consensus organizations (NIOSH, ASTM, CFR). There are no human "experts" establishing a subjective ground truth for these specific performance metrics.
4. Adjudication Method for the Test Set
This section is not applicable. Adjudication methods like 2+1 or 3+1 are typically used for subjective assessments or when there's ambiguity in classifying data, common in medical imaging or pathology. For physical performance tests of a mask, the results are quantitative measurements or pass/fail decisions based on objective criteria, not requiring expert adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance
This section is not applicable. An MRMC study is relevant to AI/software products that assist human readers (e.g., radiologists, pathologists). This submission is for a physical medical device (respirator/mask) and does not involve AI or human readers.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
This section is not applicable. This device is a physical product and does not involve an algorithm.
7. The Type of Ground Truth Used
The ground truth used is based on objective physical and performance test results derived from standardized laboratory methods (e.g., NIOSH, ASTM) against predefined quantitative thresholds. For example, for "Filter Efficiency," the ground truth is the measured percentage of particles filtered, compared to the >95% criterion. For "Fluid Resistance," it's the observation of synthetic blood penetration.
8. The Sample Size for the Training Set
This section is not applicable. This is a physical device and does not involve a "training set" in the context of machine learning. The manufacturing process is likely subject to quality control and design verification, but this is distinct from "training data."
9. How the Ground Truth for the Training Set Was Established
This section is not applicable as there is no "training set" for this device.
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