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The Electric Breast Pump (F5055) is intended to express milk from lactating women and collect milk from their breast. The device is intended for single user.

The Electric Breast Pump (F5055) is a powered breast pump to be used by lactating women to express and collect milk from their breast. The Electric Breast Pump (F5055) is intended for a single user. The proposed device is electrically powered and software-controlled. The device operates via a microprocessor-driven air pump, which generates suction on the breast to extract milk. The proposed device is available in one model, F5055. The provided non-sterile and is not to be sterilized by the user prior to use. The device includes a breast shield assembly, bottles, pump unit, tubing, an adapter, and pump unit. The breast shield assembly includes a silicone breast shield and polypropylene breast shield body that contacts the user's breast.

The provided text is a 510(k) Summary for an Electric Breast Pump (F5055). This document details the manufacturer's claim of substantial equivalence to a predicate device, as required for FDA premarket notification.

However, the provided text does not contain information related to an AI/ML powered medical device, nor does it discuss acceptance criteria and a study proving the device meets those criteria in the context of AI/ML performance. The device described is an "Electric Breast Pump," a hardware device with software controls, but it does not appear to involve AI or machine learning for diagnostic or assistive functions that would require the typical performance study details asked in the prompt.

Therefore, I cannot fulfill the request for information on acceptance criteria and a study proving an AI/ML device's performance based on the provided text, as the text describes a non-AI/ML medical device.

To directly answer your prompt based on the provided text, focusing on the type of acceptance criteria and performance testing presented for this specific device (an electric breast pump):

The acceptance criteria for this medical device are primarily focused on safety and effectiveness as demonstrated through non-clinical performance testing, and comparison of technological characteristics and indications for use with a legally marketed predicate device.

Here's a breakdown of the "acceptance criteria" (implicitly, the aspects where the device must perform acceptably) and the study/testing performed, as per the document, rather than a typical AI/ML study:

Acceptance Criteria and Reported Device Performance (as inferred for an Electric Breast Pump):

Regarding the specific questions posed, adapted to the context of this non-AI/ML device:

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

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

   • The document does not specify sample sizes for the non-clinical performance tests (e.g., how many units were tested for electrical safety, or how many cycles for pump performance).
   • Data provenance is not explicitly stated in terms of country of origin for the testing itself, nor is it described as retrospective or prospective data collection from human subjects. The tests are non-clinical, so they are likely laboratory-based.

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

   • This question is largely not applicable to this type of device and testing. There is no "ground truth" establishment by experts in the sense of image interpretation or diagnostic accuracy.
   • The "ground truth" for non-clinical performance testing typically refers to the established engineering specifications and international standards (e.g., IEC, ISO) that the device must meet. The "experts" involved would be qualified test engineers and quality assurance personnel performing and verifying these tests. Their qualifications are not detailed in this summary.

4. Adjudication method for the test set:

   • This is not applicable as there is no subjective interpretation or consensus process like in clinical image review. Performance criteria are objective and quantitative (e.g., measured suction strength within a range, successful completion of electrical safety tests).

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:

   • Definitely not applicable. This is not an AI/ML diagnostic or assistive device. No human reader studies (MRMC) are mentioned or necessary for this type of product.

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

   • Not applicable in the context of AI/ML algorithm performance. The "standalone" performance here refers to the device itself meeting its engineering specifications rather than an algorithm's diagnostic accuracy. The non-clinical tests (suction strength, cycle speed, etc.) represent the standalone performance of the device.

7. The type of ground truth used:

   • For this device, the "ground truth" is defined by engineering specifications, international safety standards (IEC, ISO), and functional requirements. For example, a certain suction strength is a specified operating range, and the test verifies the device achieves this.

8. The sample size for the training set:

   • Not applicable. This device does not use a "training set" in the sense of machine learning. The design and development process for such a hardware device involves prototyping, testing, and refinement, but not machine learning training on a dataset.

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

   • Not applicable, as there is no training set for an AI/ML model for this device. Ground truth for the device's functionality is established by engineering and regulatory standards.

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