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The Wearable Breast Pump (Model S32) 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 Wearable Breast Pump (Model S32), is an electrically powered wearable single breast pump consisting of the following key components: a flange, pump motor, silicone diaphragm, milk collector, bra adjustment buckle, valve, 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, expression, massage, and auto modes and control the vacuum levels within those modes. All available modes consist of 9 vacuum levels. The S32 model is capable of providing vacuum levels from 40-120 mmHg with cycling rates from 86-110 cycles per minute in stimulation mode, vacuum levels from 120-245 mmHg with cycling rates from 33-109 cycles per minute in expression mode, vacuum levels from 40-120 mmHg with cycling rates from 90-120 cycles per minute in massage mode, and vacuum levels from 40-245 mmHg with cvcling rates from 33-120 cvcles per minute in auto mode. The model S32 Wearable Breast Pump is charged with a 5 V DC adaptor and powered by an internal rechargeable lithium-ion polymer battery. The motor unit operates on embedded software. Software updates are not supported. The subject device is for repeated use by a single user in a home environment. 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 breast pump expresses milk by creating a seal around the nipple using the flange and applying and releasing suction to the milk is collected in a milk collection container, which can be used for storage. To prevent milk from flowing into the vacuum system, a backflow protection membrane physically separates the milk-contacting pathway from the vacuum system. All other components (i.e., motor unit/housing) of the subject device are not in contact with the breast. All milk contacting components are compliant with 21 CFR 174-179.

The provided text is a 510(k) Summary for a Wearable Breast Pump (Model S32). It outlines the device's characteristics, comparison to a predicate device, and a summary of non-clinical performance testing. However, it does not include the specific details typically found in a study proving a device meets acceptance criteria, especially for a medical device involving AI, image analysis, or complex diagnostics.

The document states: "Other performance testing was conducted to show that the device meets its design requirements and performs as intended. The performance tests include:

• Vacuum level verification testing at each mode/cycle demonstrated that the devices meet mode/cycle specifications.
• Backflow protection testing was conducted to verify liquid does not backflow into the tubing.
• Use life testing was conducted to demonstrate that the device maintains its specifications ● throughout its proposed use life.
• Battery performance testing was conducted to demonstrate that the battery remains functional during its stated battery use-life.
• Battery status indicator testing was conducted to demonstrate that the battery status indicator ● remains functional during its stated battery life."

Based on the provided text, here's an attempt to answer your questions, highlighting what is present and what is absent:

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

The document broadly outlines performance tests conducted, but it does not provide explicit acceptance criteria values or the specific reported device performance results in a table format. It states that "Vacuum level verification testing at each mode/cycle demonstrated that the devices meet mode/cycle specifications." This implies that the measured vacuum levels and cycle speeds met predefined targets, but those targets (acceptance criteria) and the actual measured values (reported performance) are not detailed.

Table Placeholder (Information NOT PROVIDED in the text):

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 the sample sizes for any of the performance tests (e.g., number of units tested for vacuum levels, backflow, use life, or battery performance). It also does not mention data provenance, as this is a mechanical/electrical device, not one that processes patient data. The testing is likely lab-based internal validation rather than clinical data collection.

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 is not applicable to the type of device and testing described. Ground truth establishment by experts (like radiologists for image analysis) is relevant for AI/ML-driven diagnostic devices. For a breast pump, performance is assessed through engineering measurements (e.g., vacuum pressure, cycle speed, battery life, physical backflow).

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

Not applicable. Adjudication methods are used in studies involving human interpretation (e.g., reading medical images) where there might be disagreement among experts. For mechanical/electrical performance testing, measurements are typically objective and repeatable.

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. An MRMC study is relevant for diagnostic devices (especially those involving AI assistance to human readers/interpreters). This document is for a medical device (breast pump) that does not involve AI assistance for human interpretation or diagnosis.

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

Not applicable. The device has "embedded software" but it's for controlling the pump's operation (modes, vacuum levels, timing), not for diagnostic or analytical purposes that would require standalone algorithm performance evaluation against a "ground truth" in the typical sense of AI/ML devices.

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

For this device, "ground truth" refers to the engineering specifications and expected performance, verified through direct physical measurements. For example:

• Vacuum levels: Verified against calibrated pressure sensors.
• Cycle speed: Verified against timing mechanisms.
• Backflow protection: Verified visually or with sensors to confirm no liquid passes.
• Use life/Battery performance: Verified by running the device for specified durations and checking if performance metrics remain within tolerance.

8. The sample size for the training set

Not applicable. This device's embedded software controls the pump's mechanical functions; it is not an AI/ML model trained on a dataset. Therefore, there is no "training set" in the context of machine learning.

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

Not applicable, as there is no training set for an AI/ML model. The "ground truth" for the device's design specifications would have been established through engineering design principles, regulatory standards (e.g., IEC standards for medical electrical equipment), and a thorough understanding of the physiological requirements for breast milk expression.

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