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The 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.

The Nasal Aspirator consists of silicone tips which has three models (A, B, C), host, tube, mucus collector. The accessory are charging cable-USB, clean brush, clip, sponge. The 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 exter (not included in this device) through the provided charging line. The user interface consists of buttons and indicator/ display, and 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 describes the 510(k) summary for the Nasal Aspirator (BC-021, BC-022, BC-023, BC-024, BC-025, BC-026). It does not contain information typically found in acceptance criteria or a study design for evaluating an AI/ML powered device. Instead, it focuses on the substantial equivalence of a medical device (a nasal aspirator) to a predicate device.

Therefore, many of the requested details about acceptance criteria, study design, ground truth, and expert involvement are not applicable or cannot be extracted from this document, as it is related to a conventional medical device rather than an AI/ML-powered one requiring such extensive performance studies as described in your prompt.

Here's an attempt to answer the questions based on the limited relevant information:

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

The document does not explicitly present a table of "acceptance criteria" in the context of AI/ML performance metrics (e.g., sensitivity, specificity). Instead, it discusses the equivalence of technological characteristics and performance tests for a physical device.

2. Sample size used for the test set and the data provenance

Not applicable. The document describes tests for a physical medical device (Nasal Aspirator), not an AI/ML algorithm requiring a test set of data. The "tests" mentioned are product appearance tests, performance tests, and human factors engineering verification, which typically involve a limited number of physical units or usability testing, not large datasets.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. This device is not an AI/ML system that requires expert-established ground truth from a test set of data.

4. Adjudication method for the test set

Not applicable. This device is not an AI/ML system that requires adjudication of a test set.

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-assisted device, so an MRMC study comparing human readers with and without AI assistance is irrelevant.

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

Not applicable. The device is a physical nasal aspirator, not an algorithm.

7. The type of ground truth used

Not applicable in the context of AI/ML. For a physical device, "ground truth" would be related to physical measurements and compliance with established engineering and safety standards (e.g., the actual vacuum pressure measured, adherence to IEC standards).

8. The sample size for the training set

Not applicable. This is a physical medical device, not an AI/ML algorithm that requires a training set.

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

Not applicable. This is a physical medical device, not an AI/ML algorithm.

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The BASEN™ Wearable Breast Pump (Model: YM-801, YM-805, YM-805, YM-806, YM-808) is intended to express milk from lactating women in order to collect milk from their breasts. The device is intended for a single user.

The BASEN™ Wearable Breast Pump is an electrically powered wearable breast pump consisting of the following key components: pump, pump diaphragm, container valve, 5-ounce (150 milliliter) container bowl, flange, seal ring, joint pipe, and USB charging cable. It is designed to work in the user's bra and has a rechargeable battery so it can be used hands-free without any external power cords. The motor unit includes a press-button user interface, pump body, and LED display. Pumping can be performed on one breast (single pumping). The user interface allows the user to switch from stimulation, massage mode, and expression mode and control the vacuum levels within those modes.

Both stimulation and expression mode consist of 9 vacuum levels. The pump can provide vacuum levels from -40 to -105 mmHg with cycling rates from 70 to 114 cycles per minute in stimulation and massage mode. Expression mode had vacuum levels from -40 to -245 mmHg with cycling rates from 23 to 90 cycles per minute.

The motor unit operates on embedded software. Software updates by end-users are not supported. The subject device is for repeated use by a single user in a home environment. The breast pump expresses by creating a seal around the nipple using the flange and applying and releasing suction to the nipple. The milk is collection container bowl. To prevent milk from flowing into the vacuum system, a backflow protection membrane physically separates the milk-contacting pathway from the vacuum system. The device is provided not sterile.

The motor unit operates on a rechargeable battery and does not function when charging. The rechargeable battery can be charged from the external USB adapter if the motor unit is not in operation.

The subject device components are made of the following materials:

• . Motor unit: Acrylonitrile Butadiene Styrene (ABS) plastic
• . Flange, tube, valve, diaphragm: Silicone
• Linker, milk collection container: Polypropylene

All milk contacting components are compliant with 21 CFR 174-179.

It seems there's a misunderstanding based on the provided document. The document describes a 510(k) premarket notification for a medical device (a breast pump), and it focuses on demonstrating substantial equivalence to a predicate device.

Crucially, this document does not contain information about acceptance criteria for an AI/ML powered device, nor does it describe a study specifically proving that an AI/powered device meets such criteria.

The "Software" section on page 9 states: "Software was evaluated at a basic documentation level as recommended in the 2023 FDA guidance document 'Guidance for the Content of Premarket Submissions for device software function.'" This indicates that the software in this breast pump is likely embedded software controlling its basic mechanical functions (like motor control, vacuum levels, and modes), rather than an AI/ML algorithm performing diagnostic or predictive tasks that would require the kind of extensive clinical validation, ground truth establishment, and MRMC studies you're asking about.

Therefore, I cannot extract the information requested about acceptance criteria and a study proving an AI/ML device meets them from this document.

If you have a document pertaining to an AI/ML medical device, please provide that, and I would be happy to help answer your questions.

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