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The Lactaline Personal Powered Breast Pumps (Premier/Expresse) are intended to express and collect the mother's milk of a nursing woman for the purpose of feeding the collected milk to a baby.

The Expresse and Premier powered breast pumps are intended to express the mother's milk of a nursing woman. The pumping can be performed on one breast or both breasts at the same time. A control knob adjusts the suction strength (vacuum) to one of 8 settings between <100 and 360 mbar. Another control knob adjusts the suction rhythm (cycle) to one of 4 settings from 30 to 60 cycles per minute. The difference between the Premier and Expresse are the special bottle holders on the Expresse for using Freezer bags. All other features are substantially equivalent (Software, size, suction capacity, control knobs, weight, noise level and power supply.)

The provided document is a 510(k) premarket notification for the Ameda Egnell Powered Breast Pumps (Expresse and Premier). This document focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed study proving the device meets specific performance acceptance criteria through clinical trials or extensive standalone testing.

Therefore, much of the requested information (acceptance criteria, specific study details, sample sizes, expert qualifications, adjudication methods, MRMC studies, specific ground truth methods for training/testing sets) is not explicitly available within the provided text.

However, based on the information provided, I can infer what constitutes "acceptance" for this regulatory submission and extract the performance characteristics presented for comparison.

Here's a breakdown of what can be inferred and what is not available:

1. Table of Acceptance Criteria and Reported Device Performance

For a 510(k), "acceptance criteria" are generally met when the proposed device demonstrates substantial equivalence to legally marketed predicate devices, particularly concerning intended use, technological characteristics, and safety/effectiveness. The table provided is a comparison of technological characteristics to establish this equivalence, rather than a list of "acceptance criteria" in the traditional sense of performance targets.

Note: The "Acceptance" column here reflects the range or type of characteristics seen in the predicate devices, which the proposed devices aim to match or fall within, thereby demonstrating substantial equivalence.

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

Not applicable/Not provided in the document. This is a 510(k) submission based on technological characteristics and comparison to predicate devices, not typically involving a test set of data from human subjects for performance evaluation like an AI/medical imaging device. Device performance is inferred from design and comparison.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable/Not provided. The ground truth for this submission is regulatory compliance and established performance of predicate devices. There wouldn't be a "ground truth" derived from expert review of output in the way one would for an AI performance study.

4. Adjudication Method

Not applicable/Not provided.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC study was not done or reported in this document. This submission does not involve AI assistance for human readers.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not applicable. This is a mechanical/electronic medical device, not an algorithm. Performance is demonstrated through technical specifications and comparison, not standalone algorithm performance testing.

7. The Type of Ground Truth Used

The "ground truth" for this 510(k) submission is the established safety and effectiveness of the identified predicate devices as determined by prior FDA clearances and regulatory standards (e.g., 21 CFR 884.5160 for intended use). The applicant argues that their device's technological characteristics are sufficiently similar to these predicates.

8. The Sample Size for the Training Set

Not applicable/Not provided. Training sets are relevant for AI/machine learning models, which this device is not.

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

Not applicable/Not provided.

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