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The Electric Nasal Aspirator is intended for intermittent removal of nasal secretions and mucus from children (age 2~12 years old). This device is used in a home environment.

Electric Nasal Aspirator consists of silicone nozzle which has three models (conical nozzle, flat nozzle, angled nozzle), collection cup, air tube, tweezers, charging cable-USB and aspirator body. The Electric Nasal Aspirator is a portable device which is intended for suction of nasal passages in children 2-12 years of age. The motor pump provides a negative pressure which removes nasal secretions. The motor pump operates on a rechargeable battery. The rechargeable battery can be charged from the external power adapter (not included in this device) through the provided charging line.

The user interface consists of buttons and LED display, and the user can control the vacuum pressure through the button. Three different shapes of silicone nasal tips are provided to enable easier and more effective removal of the nasal mucus.

The provided text is a 510(k) clearance letter and summary for an Electric Nasal Aspirator. It details the device's characteristics and its comparison to a predicate device, along with the performance data submitted to demonstrate substantial equivalence.

However, the nature of this medical device (a nasal aspirator, essentially a suction pump) means the "acceptance criteria" and "study that proves the device meets the acceptance criteria" are focused on engineering performance parameters (e.g., vacuum pressure, flow rate, safety standards) rather than clinical efficacy studies with human subjects that measure the device's ability to diagnose or treat a condition, which is what is typically discussed in the context of "human-in-the-loop performance," "ground truth," "expert consensus," and "MRMC studies" for AI/software-as-a-medical-device (SaMD).

Therefore, the requested information elements related to AI/SaMD (e.g., training set, test set, expert adjudication, MRMC studies, standalone performance, ground truth for image analysis) are not applicable to this specific device submission. The "study" here is a series of bench tests and electrical/biocompatibility assessments.

Below is a breakdown of the applicable acceptance criteria and the "study" (bench testing) as described in the provided text, while explicitly stating when an element is not applicable.

Acceptance Criteria and Device Performance for Electric Nasal Aspirator (K244033)

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated as a number of devices tested. The studies described are type testing (verification and validation) against engineering standards (e.g., IEC, ISO). This implies a representative sample of manufactured devices were tested to ensure design compliance. For biocompatibility, electrical safety, EMC, battery safety, and software V&V, these are typically conducted on a limited number of devices or components to demonstrate compliance with the standards' requirements for design verification.
• Data Provenance: The device manufacturer, Shenzhen Desida Technology Co., Ltd. (China), performed these tests. The data provenance is internal testing to support the 510(k) submission. These are bench tests, not clinical data.
  • Retrospective/Prospective: Not applicable as these are bench tests and not clinical studies involving patient data collected over time.

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

• Not Applicable. For this type of medical device (Electric Nasal Aspirator), "ground truth" as typically applied to clinical or diagnostic AI/SaMD studies (e.g., for image interpretation) is not established through expert consensus on a test set. The validation relies on meeting pre-defined engineering and safety standards. The "experts" involved would be accredited test houses and engineers specializing in the relevant standards (e.g., electrical safety, biocompatibility).

4. Adjudication Method for the Test Set

• Not Applicable. Adjudication methods (e.g., 2+1, 3+1) are used in clinical studies, particularly for establishing ground truth in diagnostic accuracy assessments involving human interpretation. This device's validation focuses on engineering performance, not interpretative accuracy.

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

• Not Applicable. This is not an AI/SaMD device, and no MRMC study was conducted. The device is a physical product for suction, not a diagnostic or interpretive tool.

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

• Not Applicable. This is not an algorithm-based device. Performance testing for this device is "standalone" in the sense that the device itself is tested against its specifications and relevant safety standards, without continuous human operation being part of the assessment of device performance (though a human operates it to perform the tests).

7. The Type of Ground Truth Used

• Engineering and Safety Standards: The "ground truth" for this device's acceptance is adherence to established international and national engineering standards (e.g., IEC 60601-1, IEC 60601-1-2, IEC 60601-1-11, IEC 62133-2, ISO 10993 series) and the manufacturer's own verified product requirements derived from these standards and the predicate device's performance. For biocompatibility, this typically involves laboratory assays confirming the absence of cytotoxicity, skin sensitization, and irritation based on ISO 10993 protocols. For physical properties, it involves measurements against specified ranges (e.g., 52-60 KPa vacuum pressure).
• Not clinical outcomes data, pathology, or expert consensus (in the traditional sense for diagnostic/AI devices).

8. The Sample Size for the Training Set

• Not Applicable. This device is a physical product, not an AI/Software device requiring a "training set."

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

• Not Applicable. As there is no "training set" for this physical device, there is no ground truth established for it in the context of machine learning. The device's design and manufacturing processes are validated against engineering principles and standards.

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