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The Youha electric breast pumps (The INs, The INs Gen2, The INs NEXT, and P3) and BEBEBAO electric breast pump (P1s) are powered breast pumps intended to be used by lactating women to express and collect milk from their breasts. They are intended for a single user.

The subject devices are wearable-style breast pumps designed for lactating women to express and collect milk from the breast. They are electrically powered, software controlled, digital pumps for a single user. The subject devices include The INs, The INs Gen 2, The INs NEXT, P1s, and P3 models, which are capable of expression, massage, and mixed modes with ten associated suction levels for each. All five models have a single pumping configuration and can be operated in 'normal' or 'quiet' modes.
Massage, expression, and mixed pumping modes consist of 10 vacuum levels. Each Youha and BEBEBAO electric breast pump model is capable of providing vacuum levels from 40-190 mmHg with cycling rates from 90-110 cycles per minute in massage mode, vacuum levels from 80-280 mmHg with cycling rates from 40-75 cycles per minute in expression mode, and vacuum levels from 80-280 mmHg with cycling rates from 6-46 cycles per minute in mixed mode. The Youha electric 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 by end-users are not supported. The subject devices do not have wireless capability or other external functionality (i.e., no Bluetooth or mobile application). 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 can function when charging.
The breast pump expresses milk by creating a seal around the nipple using the breast shield and applying and releasing suction to the nipple. 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 FDA 510(k) summary for the Youha electric breast pumps (K242725) outlines the device's technical specifications and the non-clinical performance testing conducted to demonstrate substantial equivalence to a predicate device. However, this document does not detail acceptance criteria and a study proving that the device meets those acceptance criteria in the context of an AI/ML medical device, as it is a powered breast pump, not an AI/ML system.

The prompt's request for detailed information such as "sample size used for the test set," "number of experts used to establish ground truth," "MRMC comparative effectiveness study," and "standalone (algorithm only) performance" are typical requirements for the validation of AI/ML-driven medical devices, particularly those involving image analysis or diagnostic support.

Since the Youha electric breast pump is a physical device with a software component that controls its operation (massage, expression, mixed modes, vacuum levels, cycle speeds), and not an AI/ML diagnostic or therapeutic device, the requested information (acceptance criteria for AI performance, clinical study results comparing AI-assisted vs. non-AI scenarios, etc.) is not applicable to this type of submission.

Therefore, I cannot fulfill the request to describe the acceptance criteria and the study that proves the device meets the acceptance criteria (as defined for an AI/ML device) using the provided document. The document focuses on performance testing relevant to a mechanical/electronic medical device, such as biocompatibility, electrical safety, electromagnetic compatibility, software validation (at a basic documentation level, not AI performance), vacuum level verification, backflow protection, use life, and battery performance.

To answer your specific questions based on the provided document and its scope:

1. A table of acceptance criteria and the reported device performance:
   The document describes various performance tests and implies their acceptance criteria are met (e.g., "Vacuum level verification testing at each mode/cycle demonstrated that the devices meet mode/cycle specifications."). However, it does not present these in a formal table of acceptance criteria vs. specific reported values in the way one would for an AI/ML device's diagnostic performance (e.g., sensitivity, specificity, AUC).

   • Examples of Implicit Acceptance Criteria and Performance (derived from "Performance Testing" section):

     Acceptance Criteria (Implied)	Reported Device Performance
     Device meets mode/cycle specifications for vacuum levels.	"Vacuum level verification testing at each mode/cycle demonstrated that the devices meet mode/cycle specifications."
     No liquid backflow into tubing.	"Backflow protection testing was conducted to verify liquid does not backflow into the tubing."
     Device maintains specifications throughout proposed use life.	"Use life testing was conducted to demonstrate that the device maintains its specifications throughout its proposed use life."
     Battery remains functional during stated battery use-life.	"Battery performance testing was conducted to demonstrate that the battery remains functional during its stated battery use-life."
     Battery status indicator remains functional during stated battery life.	"Battery status indicator testing was conducted to demonstrate that the battery status indicator remains functional during its stated battery life."

2. Sample sized used for the test set and the data provenance: Not applicable in the context of AI/ML test sets. The testing here refers to physical device units rather than data samples for an algorithm. The document does not specify the number of physical units tested for each non-clinical test.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as typically defined for AI/ML (e.g., for disease detection or image interpretation) is not established for a breast pump's functional performance.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. This refers to consensus methods for establishing ground truth in AI/ML studies.

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 specific to AI/ML devices that assist human interpretation.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. The device's software controls its mechanical function; it's not a standalone diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable in the AI/ML sense. The "ground truth" for this device's performance would be engineering specifications and validated physical measurements (e.g., actual vacuum levels vs. specified, absence of backflow).

8. The sample size for the training set: Not applicable. The "software" mentioned refers to embedded code controlling the hardware, not a machine learning model that requires a training set.

9. How the ground truth for the training set was established: Not applicable for the reasons stated above.

In summary, the provided document details a 510(k) submission for an electric breast pump, which is a traditional medical device regulated under 21 CFR 884.5160 as a Class II powered breast pump. The testing described (biocompatibility, electrical safety, EMC, software validation at a basic level, and performance tests for vacuum, backflow, life, and battery) is appropriate for this type of device. The questions posed in the prompt are tailored for AI/ML device submissions, which are not relevant to this specific FDA clearance document.

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The electric breast pumps are intended to be used by lactating women to express and collect milk from their breasts. They are intended for a single user. The electric breast pumps are intended for at home use.

The Youha, Bebebao, and Yiyadodo electric breast pumps are single-user, powered breast pump intended to be used by lactating women to express and collect milk from their breasts. THE ONE, YH-8012, BB-5020 and YY-5030 have both single (pumping from one breast) and double pumping (pumping from both breasts) configurations. YY-8011 and YH-8019 have a single pumping configuration only. A reciprocating diaphragm vacuum pump, driven by a microprocessor, generates the suction to extract the milk at vacuum levels up to 280 mmHg. The user interface for the THE ONE, YH-8012, BB-5020 and YY-5030 models consists of a front panel keypad and LCD display or LED display in which the user switches between modes and controls the vacuum pressure. The YY-5030 model does not have any visual indicators on the pump housing. The device has three modes of operation: Massage mode: Suction patterns with fast cycles and low vacuum to start milk flowing; Low expression mode: Suction patterns with slow cycles and high vacuum to express more milk gently and efficiently; High expression mode: Suction patterns with slower cycles and higher vacuum to express more milk efficiently. THE ONE, YH-8012 and BB-5020 have 3 modes including massage mode, low expression mode and high expression mode. YY-5030, YH-8011, and YH-8019 have 2 modes including massage mode and high expression mode. The device is electrically powered from either an internal lithium ion rechargeable battery or an external AC power adapter. The external adapter also charges the battery.

Here's an analysis of the acceptance criteria and study information provided in the document for the Youha Electric Breast Pump (and related models):

Important Note: The provided document is a 510(k) Summary for a powered breast pump. It is not a document for an AI/ML-driven device. Therefore, many of the requested categories related to AI/ML device studies (e.g., expert adjudication, MRMC study, training set ground truth, effect size) are not applicable to this type of medical device. The information below will focus on the applicable criteria and studies described for a non-AI medical device.

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a breast pump and not an AI/ML device, the "acceptance criteria" are related to performance specifications rather than diagnostic accuracy.

The document states that "The test results demonstrated that the proposed device complies with the following standards and guidance documents" and "The specifications were met for vacuum level, cycle rate, and backflow protection for the duration of a pumping session... These specifications were maintained under conditions of single and double pumping mode with varying power sources."

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

The document describes non-clinical performance testing of the device itself (hardware and software), rather than a clinical study with human subjects or a dataset derived from humans. Therefore, the concept of a "test set" and "data provenance" (country of origin, retrospective/prospective) as typically applied to AI/ML performance studies, does not directly apply here. The testing involved measuring the device's physical and electrical properties against its design specifications and recognized standards.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts

Not applicable. As this is a non-AI/ML medical device, no expert clinical review for ground truth establishment on a test set (e.g., image interpretation) was performed. The "ground truth" for the device's physical performance was its design specifications and compliance with international standards, which would be verified by qualified engineers and technicians.

4. Adjudication Method for the Test Set

Not applicable for a non-AI/ML medical device.

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.

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.

7. The Type of Ground Truth Used

The "ground truth" for this device's performance is established by:

• Its design specifications (e.g., target vacuum levels, cycle rates).
• Compliance with international and national standards for medical device safety and performance (e.g., IEC 60601-1, IEC 60601-1-2, IEC 60601-1-11, ISO 14971, IEC 62304, FDA biocompatibility guidance).

8. The Sample Size for the Training Set

Not applicable. This is a non-AI/ML medical device, so there is no "training set" in the context of machine learning.

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

Not applicable. This is a non-AI/ML medical device.

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The Youha electric breast pump is intended to be used by lactating women to express and collect milk from their breasts. It is intended for a single user.

The Youha electric breast pump is a single-user, powered breast pump intended to be used by lactating women to express and collect milk from their breasts. YH-8004 and YH-8016 have both single (pumping from one breast) and double pumping (pumping from both breasts) configurations. YH-8006IV and YH-8015 have a single pumping configuration only.

A reciprocating diaphragm vacuum pump, driven by a microprocessor, generates the suction to extract the milk at vacuum levels up to 280mmHg. The user interface consists of a front panel keypad and LCD display in which the user switches between modes and controls the vacuum pressure.

The device has three modes of operation:

• Massage mode: Suction patterns with fast cycles and low vacuum to start milk flowing
• Low expression mode: Suction patterns with slow cycles and high vacuum to express more milk gently and efficiently.
• High expression mode: Suction patterns with slower cycles and higher vacuum to express more milk efficiently.

YH-8004, YH-8015 and YH-8016 have 3 modes including massage mode, low expression mode and high expression mode. YH-8006IV has 2 modes including massage mode and high expression mode.

The device is electrically powered from either an internal rechargeable battery or an external AC power adapter. The external adapter also charges the battery.

This document pertains to the 510(k) premarket notification for the Youha electric breast pump. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific acceptance criteria and a study to prove meeting those criteria in the context of diagnostic accuracy for an AI/ML device.

Therefore, many of the requested elements for an AI/ML device's acceptance criteria and study design are not applicable to this regulatory submission for a powered breast pump.

Here's an attempt to extract relevant information and note where the requested information is not present in this document:

1. Table of Acceptance Criteria and Reported Device Performance

For a breast pump, "acceptance criteria" generally refer to meeting specified physical and performance characteristics, safety standards, and functional requirements. These are defined internally by the manufacturer and verified through non-clinical testing. The document highlights compliance with recognized standards.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not applicable in the context of an AI/ML device's diagnostic performance evaluation. The "test set" here refers to physical testing of device units. The document states "Performance testing was conducted at minimum and maximum vacuum settings" on the device, but it does not specify the number of units tested, the number of measurements, or any details about data provenance in the way it would for AI/ML algorithm evaluation. These are typically internal verification and validation tests.

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

This is not applicable. For a breast pump, "ground truth" relates to its physical and functional performance measurements against engineering specifications, not clinical diagnostic accuracy assessed by experts.

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

This is not applicable. This relates to expert consensus for ground truth establishment in clinical studies, which is not relevant for a breast pump's functional testing.

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

This is not applicable. An MRMC study is relevant for evaluating the impact of AI on human diagnostic performance, which is not the purpose of this submission for a breast pump.

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

This is not applicable. This refers to AI algorithm performance evaluation, not a physical medical device like a breast pump.

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

The "ground truth" for the breast pump's performance is derived from engineering specifications and recognized national/international standards (e.g., vacuum levels, cycle rates, electrical safety parameters, biocompatibility limits). The document states: "Performance testing was conducted at minimum and maximum vacuum settings to determine the minimum and maximum vacuum levels of the pump as compared to its specifications. The specifications were met for vacuum level, cycle rate, and backflow protection."

8. The sample size for the training set

This is not applicable. A breast pump does not use a "training set" in the sense of machine learning. Its design is based on engineering principles and verified through physical testing.

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

This is not applicable. See point 8.

Summary of the Study (as described in the document for substantiating equivalence):

The "study" described in the document is a series of non-clinical performance tests conducted by the manufacturer to verify that the Youha electric breast pump meets its design specifications and complies with relevant safety and performance standards. It is a verification and validation (V&V) process rather than a clinical study or AI algorithm evaluation.

• Objective: To verify that the Youha electric breast pump met all design specifications and is substantially equivalent to the predicate device (Spectra 9 Plus powered breast pump).
• Methods: Physical testing was performed to assess:
  • Compliance with various international standards for risk analysis (ISO 14971), electrical safety (IEC 60601-1, AAMI/ANSI ES 60601-1), electromagnetic compatibility (IEC 60601-1-2), home use safety (IEC 60601-1-11), and biocompatibility (ISO-10993 parts 5 and 10).
  • Software validation according to IEC 62304 and FDA guidance.
  • Performance characteristics such as minimum and maximum vacuum levels, cycle rate, and backflow protection under different conditions (minimum/maximum vacuum settings, single/double pumping mode, AC/DC vs. battery power).
• Results: The test results demonstrated that the proposed device complies with the listed standards and met its specifications for vacuum level, cycle rate, and backflow protection under various operating conditions.
• Conclusion: Based on the comparison with the predicate device and the non-clinical test results, the Youha electric breast pump was deemed substantially equivalent to the predicate device.

Key takeaway for AI/ML context: This document is an example of a 510(k) submission for a traditional medical device, not a software as a medical device (SaMD) or an AI/ML-driven device. Therefore, the requirements for demonstrating diagnostic accuracy and clinical performance for AI/ML are inherently different and not addressed here.

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