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The TT Electric Breast Pump and TT Double Electric Breast Pump are intended to express and collect milk from the breast of a lactating woman. This powered breast pump is intended for a single user and is intended to be used in a home environment.

The TT Electric Breast Pump and TT Double Electric Breast Pump are intended to express and collect milk from the breast of a lactating woman. The devices are intended for a single user. The subject devices are for repeated use by a single user and are for use in home and professional healthcare environments. The devices are not sterile. The subject devices are electrically powered double (TT Double Electric Breast Pump) and single (TT Electric Breast Pump) breast pumps consisting of the following key components: a motor unit with a press-button user interface, pump body, LCD display, air tube connectors, and breast milk collection bottles. The motor unit operates on embedded software. Software updates by end-users are not supported. The breast pump extracts milk from the breasts by creating a seal around the nipple and applying and releasing suction to the nipple. The milk is collection container, which can be used for storage. To prevent milk from flowing into the vacuum system, a protection membrane physically separates the milkcontacting pathway from the vacuum system. The motor unit operates on a rechargeable battery or on an external mains adapter that is provided with the system via a micro-USB type connection. The rechargeable battery can be charged from the external mains adapter if the motor unit is not in operation. All other components of the subject devices are not in contact with the breast.

The provided text is a 510(k) Summary for the TT Electric Breast Pump and TT Double Electric Breast Pump. It does not describe an AI/ML powered device, but rather a powered breast pump. Therefore, many of the requested categories for AI/ML device descriptions, such as "number of experts used to establish ground truth," "adjudication method," "MRMC study," "stand-alone study," "ground truth used," "training set sample size," and "training set ground truth establishment," are not applicable to this document.

However, I can extract information related to the acceptance criteria and performance testing for this non-AI device.

Here's the information extracted from the document, focusing on the acceptance criteria and performance testing:

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

The document does not explicitly present a table of "acceptance criteria" alongside "reported device performance" in a quantitative manner as one might find for an AI/ML algorithm's metrics (e.g., sensitivity, specificity thresholds). Instead, it describes performance tests conducted to demonstrate that the device meets its design requirements and performs as intended, and that it is as safe and effective as the predicate device.

The "acceptance criteria" are implied by the successful completion of the listed tests and the comparison to the predicate device's specifications. The "reported device performance" is the successful outcome of these tests.

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 sample sizes for any of the performance tests (e.g., how many devices were tested for vacuum levels, backflow, or biocompatibility). It describes the types of tests performed on the device itself.

Data provenance is not mentioned, as these are technical performance tests of the physical device, not typically involving "data provenance" in the clinical data sense. The manufacturer is Wuxi Xinzhongrui Baby Supplies Co., Ltd. in China.

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)

Not applicable. This is not an AI/ML device, and "ground truth" in the context of expert consensus in radiology, for example, is not relevant here. The ground truth for device performance is based on established engineering and medical device standards (e.g., vacuum pressure ranges, electrical safety standards).

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

Not applicable. This is not an AI/ML device requiring expert adjudication of outputs.

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/ML device.

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

Not applicable. This is not an AI/ML device. While the device has "embedded software," its performance evaluation is not framed as an "algorithm only" study in the context of an AI/ML submission.

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

Not applicable. The "ground truth" for the performance tests (e.g., vacuum levels, electrical safety, biocompatibility) are defined by established international standards (ISO, IEC, AAMI ANSI ES60601-1) and the device's own design specifications compared to a predicate device.

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no "training set."

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

Not applicable. This is not an AI/ML device, so there is no "training set" or "ground truth" established for it in that context.

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The powered Electric Double Breast Pumps are intended to express and collect milk from the breast of a lactating woman. They are double pumps with a single pumping option and intended for single user.

The Electric Double Breast Pumps are designed and manufactured to express and collect milk from a lactating woman's breast. Both models, XB-8636 and XB-8703, are electrically powered, softwarecontrolled, digital single-user pumps.

When powered, the XB-8636 starts with stimulation mode for 120 seconds then automatically switches to expression mode for 30 minutes before automatic shutdown. This model has seven suction levels. When powered, the XB-8703 starts with stimulation mode for 180 seconds then automatically switches to expression mode for 30 minutes before automatic shutdown. This model has nine suction levels. Both models allow the user to adjust the suction levels when necessary.

This document is a 510(k) premarket notification for an Electric Double Breast Pump. It does not describe a study involving humans or AI for diagnostic purposes. Therefore, most of the requested information regarding acceptance criteria, study details, and AI performance will not be applicable.

However, I can extract the non-clinical acceptance criteria and the summary of non-clinical tests performed to meet those criteria.

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

Based on the document, the acceptance criteria are implicit in compliance with recognized standards and design specifications. The performance reported is that the device met these specifications and standards.

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

The document does not specify sample sizes for non-clinical tests (e.g., how many units were tested for use-life, backflow, or suction curves). The tests are entirely non-clinical/bench tests. Data provenance is implied to be from the manufacturer's internal testing in China (Wuxi Xinzhongrui Baby Supplies Co., Ltd).

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 a breast pump, and the evaluation involves engineering and safety standards, not medical diagnostic "ground truth" established by experts in the context of a clinical study or AI performance evaluation.

4. Adjudication method for the test set

Not applicable, as this is not a study involving human or AI interpretation of data requiring adjudication.

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

No. This document pertains to the regulatory clearance of a physical medical device (breast pump) and does not involve AI or human readers for diagnostic interpretation.

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

No. This document does not describe the evaluation of an algorithm.

7. The type of ground truth used

For the non-clinical tests performed:

• Engineering specifications and recognized international standards: This serves as the "ground truth" or benchmark against which the device's performance was measured for safety and efficacy from an engineering perspective. For example, IEC standards define acceptable limits for electrical safety and EMC.
• Design Specifications: The manufacturer's own design specifications for parameters like suction curves, backflow prevention, and use-life were used.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning study.

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

Not applicable. This is not an AI/machine learning study.

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The powered Megna Breast Pumps are intended to express and collect milk from the breast of a lactating woman. The M5 model is a single pump. The M7, M10, and M12 models are double pumps with a single pumping option. All models are intended for single users.

The Megna breast pumps are electrically powered breast pumps for over-the-counter use, intended to be used at home to express a nursing mother's breast milk. The Megna breast pumps are provided in 4 models: Model M5 - Megna Digital Single Breast Pump, Model M7 Megna Digital Double Breast Pump, Model M10 - Megna Digital Double Breast Pump, Model M12 - Megna Digital Double Breast Pump.

The provided text describes a 510(k) premarket notification for Megna Breast Pumps (Models M5, M7, M10, and M12), which are powered breast pumps. The document focuses on demonstrating substantial equivalence to a predicate device (K113664, Closer to Nature Electric Breast Pump).

Here's an analysis based on your request:

Acceptance Criteria and Device Performance:

The document primarily focuses on demonstrating that the Megna Breast Pumps meet various safety and performance standards equivalent to a predicate device, rather than defining specific diagnostic acceptance criteria for an AI/ML device.

1. Table of Acceptance Criteria and Reported Device Performance:

Since this document is for a breast pump, the "acceptance criteria" are related to safety, electrical performance, biocompatibility, and functional specifications, compared to a predicate device. The "reported device performance" are the results of these tests and comparisons.

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

The document pertains to the regulatory clearance of a physical medical device (breast pump), not an AI/ML algorithm that processes diagnostic images or data. Therefore, the concept of a "test set" in the context of an AI/ML model's performance on patient data is not applicable here. The "tests" mentioned are engineering and material compatibility tests performed on the device components or prototypes. No information on "data provenance" (country of origin, retrospective/prospective) for clinical or diagnostic data is provided because such data is not relevant to this type of device clearance based on the provided text.

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

This information is not applicable. The device is a breast pump, not an AI/ML diagnostic or predictive tool. "Ground truth" in the context of expert consensus on medical conditions is not relevant here. The "truth" is established by adherence to engineering standards, material safety regulations, and a comparison to the functional specifications of a legally marketed predicate device.

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

Not applicable for a physical device clearance. Adjudication methods are typically used in clinical studies to resolve disagreements among experts when establishing ground truth for diagnostic AI/ML systems.

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 a breast pump, not an AI-assisted diagnostic tool.

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

Not applicable. This is not an AI/ML algorithm.

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

The "ground truth" for this device clearance is adherence to established regulatory standards (e.g., 21 CFR, ISO 10993, IEC 60601, EN 60601), successful completion of specific engineering and material tests, and demonstrable functional equivalence to a legally marketed predicate device. There is no biological or diagnostic "ground truth" in the AI/ML sense.

8. The sample size for the training set:

Not applicable. This is a physical device, not an AI/ML model that undergoes training.

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

Not applicable. No AI/ML training set is mentioned or implied.

In summary, the provided document is a 510(k) summary for a powered breast pump. It details the device's compliance with various safety and performance standards and its substantial equivalence to a predicate device, rather than addressing the specific criteria and study design relevant to AI/ML device validation.

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