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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 Pump (Model LD-208L, LD-3010L, LD-3010, LD-2010) is a powered breast pump to be used by lactating women to express and collect milk from their breasts. The Electric Breast Pump is intended for a single user.

The Electric Breast Pump (LD-208L, LD-3010L, LD-3010, LD-3010, LD-2010) is an electrically powered breast pump to be used in a home environment by a single user. The device is provided non-sterile and can be used on one breast (single pumping) or on both breasts at the same time (double pumping).

The subject devices are capable of expression, stimulation, and the hybrid 'bionio' and 'variable frequency' modes. Stimulation mode is associated with six suction levels, and expression, bionic, and variable frequency modes are associated with nine suction levels. The subject devices feature various combinations of on/off buttons, level up/down buttons, mode selection buttons, suction level/time indicators, battery visual indicator display, and mode displays. The LD-208L, LD-3010L, and LD-2010L pumps are powered by internal, nonreplaceable, rechargeable lithium-ion batteries which are charged using the included AC power supply and cable. The LD-2010 and LD-3010 are powered by alkaline batteries or AC power.

The breast pumps use cyclic negative pressure (suction) to mimic the suckling patterns of a feeding infant. A DC motor drives a membrane vacuum pump to generate the suction required to stimulate and express breast milk. The timing of this pattern is dependent upon the suction/speed settings selected by the user and is pre-programmed in the devices. The devices are capable of producing peak suction levels between -40 and -290 mmHg at speeds between 20 and 120 cycles per minute. The subject device ensures backflow protection between the breast shield and the electronic components via a physical barrier (silicone diaphragm) mechanism.

All other components (i.e., motor unit) of the subject device are not in contact with the breast. All milk contacting components are compliant with 21 CFR 177.

The provided document is a 510(k) summary for an Electric Breast Pump (LD-208L, LD-3010L, LD-2010L, LD-3010, LD-2010). This type of regulatory submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving independent effectiveness or advanced performance metrics typically associated with AI/ML devices. Therefore, much of the information requested in your prompt (e.g., sample size for test sets, expert ground truth, MRMC studies, standalone performance with effect sizes) is not applicable or generally required for a 510(k) clearance of a mechanical device like a breast pump.

Here's the information that can be extracted or inferred from the provided text:

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

For a breast pump, the "acceptance criteria" and "device performance" are primarily based on meeting safety standards, functional specifications, and demonstrating equivalence to a predicate. The document highlights various tests performed to ensure this.

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

The document does not specify sample sizes for the performance tests (e.g., how many units were tested for vacuum levels, how many use-life cycles). Data provenance details (country of origin, retrospective/prospective) are not provided as these are primarily engineering performance tests rather than clinical studies on patient data.

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

Not applicable. The ground truth for these performance tests is based on engineering specifications and adherence to international standards, not expert clinical consensus.

4. Adjudication method for the test set

Not applicable. This is not a study requiring adjudication of clinical findings.

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 device is an electric breast pump, a mechanical medical device, 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

Not applicable. This device does not use algorithms for diagnostic or interpretive performance separate from its mechanical function.

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

The ground truth for the performance testing is based on:

• Engineering specifications: Pre-defined ranges for suction levels, cycles per minute, and other functional parameters.
• International standards: Compliance with standards like ISO 10993 for biocompatibility, IEC 60601 for electrical safety, and IEC 60601-1-2 for EMC.
• Design requirements verification: Ensuring the device meets its intended design functions (e.g., backflow protection, battery function).

8. The sample size for the training set

Not applicable. There is no "training set" in the context of this 510(k) submission for a non-AI/ML device.

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

Not applicable. (See #8)

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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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The Electric Breast Pump (Models AOV6821, AOV6826, AOV6830, and AOV6852) is a powered breast pump to be used by lactating women to express and collect milk from their breast Pump is intended for a single user.

The subject devices, Electric Breast Pump (Models AOV6821, AOV6826, AOV6830, AOV6852), are powered breast pumps to be used by lactating women to express and collect milk from their breast. The proposed devices are battery powered, software-controlled, and intended for a single user. The devices are intended for home use. The subject devices have the following modes: Massage mode, Expression mode, Bionic mode, Frequency Conversion mode A, Frequency Conversion mode B, Continuous suck mode and Mixed mode; each mode has multiple levels. Massage mode is for stimulating breast milk secretion. Expression mode is for pumping breast milk. Bionic mode cycles between massaging for 2 cycles and expressing for 2 cycles. Frequency Conversion mode A cycles between massaging for 3 cycles and expressing for 1 cycle. Frequency Conversion mode B cycles between massaging for 3 cycles and expressing for 2 cycles. Continuous suck mode applies a lower suction followed by a hold and then a second increase in suction before release as a cycle. Finally, Mixed mode cycles between massaging for 3 cycles and expressing for 1 cycle at levels 1-6, then cycles between massaging for 3 cycles and expressing for 2 cycles at levels 7-9. The subject devices can be used in a single or double pumping configuration and have anti-backflow protection. The subject devices have a USB connecting cable and matching power adapter to supply power to the device. The subject devices are provided non-sterile and are not to be sterilized by the user prior to use. Each device includes a breast shield assembly, collection bottles, tubing set, feeding accessories, power adapter (for charging), and pump unit. The breast shield assembly includes a silicone breast shield and polypropylene breast shield body, which contacts the user's breast.

This is a 510(k) premarket notification for an Electric Breast Pump (Models AOV6818, AOV6821, AOV6826, AOV6830, AOV6852) and not a study detailing the development and validation of an AI/ML powered device. As such, the information requested in your prompt (acceptance criteria, study details, sample sizes, ground truth establishment, expert qualifications, adjudication methods, MRMC studies, standalone performance, and training set information) is not applicable or available within this document.

The document focuses on demonstrating substantial equivalence to a predicate device (Electric Breast Pump Models 918, HF918, K211024) through non-clinical testing. It highlights that the subject and predicate devices have the same indications for use and intended use. The non-clinical tests performed are related to the safety and performance of the physical device components, not AI/ML algorithm performance.

Here's a breakdown of the available information regarding device performance and acceptance criteria from the provided text, adapted to your table format where possible, and noting what information is not present:

1. Table of Acceptance Criteria and Reported Device Performance

• Massage mode: AOV6818: 80-200, AOV6821: 100-200, AOV6826: 80-180, AOV6830: 80-200, AOV6852: 80-200 (mmHg ±5 mmHg)
• Expression mode: AOV6818: 150-280, AOV6821: 160-280, AOV6826: 120-280, AOV6830: 120-280, AOV6852: 100-260 (mmHg ±5 mmHg) |
  | Backflow and Overflow | No liquid backflow into tubing and motor even if bottle is over-filled. | "The test results showed that there was no backflow during the test." |
  | Cycle Speed | Compliance with the design specifications of the subject devices throughout the use life. Ranges for various modes and models are listed. | "All the test results complied with the design specifications of the subject devices throughout the use life." Sample ranges include:
• Massage mode: AOV6818: 39-95, AOV6821: 36-55, AOV6826: 42-91, AOV6830: 30-98, AOV6852: 59-128 (times/Min ±2 times/Min) |
  | Battery Indicator | The battery status indicator remains functional during its stated battery life. | Battery indicator testing was conducted to demonstrate functionality. |

Since this document is a 510(k) summary for a powered breast pump (a traditional medical device), and not an AI/ML device, the following points are not applicable or derivable from the provided text:

2. Sample sizes used for the test set and the data provenance: Not applicable for a physical device's non-clinical safety/performance testing. The "test set" would be the manufactured devices and their components.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical device is established through engineering specifications and objective measurements against those specifications.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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, as this is not an AI-powered device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The "ground truth" for this device's performance would be objective measurements against engineering design specifications and relevant international standards (e.g., IEC standards for electrical safety, ISO 10993 for biocompatibility).
8. The sample size for the training set: Not applicable, as this is not an AI/ML device.
9. How the ground truth for the training set was established: Not applicable.

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The Electric Breast Pump Model: YM-8166 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 Electric Breast Pump Model: YM-8166 is an over-the-counter, non-sterile, single-user, powered breast pump intended to be used by lactating women to express and collect milk from their breasts. The device is intended for daily use in a home environment. The device uses a diaphragm-type vacuum pump driven by software embedded in the device to generate suction required to stimulate and express breast milk. The software provides control over vacuum pressure and cycle speed.

The provided text is a 510(k) summary for an Electric Breast Pump Model: YM-8166. This document focuses on demonstrating substantial equivalence to a predicate device, primarily through non-clinical performance testing related to safety and effectiveness, rather than a clinical study evaluating the accuracy or performance of an AI/ML algorithm with human-in-the-loop.

Therefore, the specific information requested in the prompt, such as acceptance criteria for AI performance, sample sizes for test sets (in the context of AI models), expert ground truth, multi-reader multi-case studies, and training set information for AI, is not applicable to this device and the provided document.

The document describes the device's technical specifications and how they compare to a predicate device, along with the results of various engineering and biological safety tests.

Here's the relevant information that can be extracted from the provided text, framed in the context of device performance, rather than AI performance:

Acceptance Criteria and Device Performance (Non-AI/ML Device)

This device, an Electric Breast Pump, is a mechanical and electrical medical device. Its "performance" is assessed based on its ability to effectively and safely express milk, primarily through its engineering specifications and biological material compatibility, not through an AI algorithm's diagnostic or predictive accuracy.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated as a "test set" in the context of an AI algorithm. For non-clinical performance testing (e.g., biocompatibility samples, electrical safety tests, functional tests), the sample sizes are implicitly defined by the testing standards and protocols used. These are typically engineering samples of the device, not a "data set" of patient cases.
• Data Provenance: The testing was conducted by the manufacturer, Guangdong Youmeng Electrical Technology Co., Ltd., based in China. The nature of these tests (e.g., bench testing, material testing) means there's no patient data involved, hence no "retrospective or prospective" designation in the AI sense.

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

• Not applicable. This device does not use an AI/ML algorithm that requires expert annotation for ground truth. The "ground truth" for this device's performance is objective measurements (e.g., electrical readings, vacuum pressure, material properties) and laboratory test results as per established engineering and biocompatibility standards.

4. Adjudication Method for the Test Set

• Not applicable. No expert adjudication is described or required for the type of non-clinical, objective performance testing conducted for this device.

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

• No. This is not an AI-assisted diagnostic device, so an MRMC study comparing human readers with and without AI assistance is not relevant or performed.

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

• Not applicable. There is no standalone AI algorithm for medical interpretation being evaluated. The device has embedded software for controlling the pump's functions (e.g., vacuum pressure, cycle speed), and its verification and validation are noted, but this is functional software, not an AI for diagnosis or treatment decision support.

7. The Type of Ground Truth Used

• Objective Measurements and Standard Compliance: The "ground truth" for this device's performance is based on established engineering specifications, published international standards (e.g., IEC for electrical safety, ISO for biocompatibility), and bench test results (e.g., vacuum pressure readings, cycle speeds, observing no backflow). It is not expert consensus, pathology, or outcomes data in the sense of clinical decision-making.

8. The Sample Size for the Training Set

• Not applicable. This is not an AI/ML device that requires a training set of data for model development. The software is noted as having "Verification and Validation" but this refers to traditional software engineering processes, not machine learning training.

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

• Not applicable. As there is no AI training set, this question is not relevant. Software "ground truth" or correct functionality is established through design specifications, requirements, and traditional software testing methodologies.

In summary, the provided document is a regulatory submission for a standard medical device (an electric breast pump) that relies on non-clinical performance testing and substantial equivalence to a predicate device, not on AI/ML algorithm performance. Therefore, many of the questions related to AI evaluation criteria are not applicable.

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The Evenflo Premium Double Electric Breast Pump (Model 4018) is an electrically powered suction device intended to express and collect milk from a lactating woman's breasts. It is intended for a single user.

The Evenflo Electric Breast Pump (Model 4018) is an electrically powered breast pump to be used in a home environment by a single user. The device is provided non-sterile and should be cleaned and disinfected prior to first use according to the instructions for use. The breast pump can be used on one breast (single pumping) or on both breasts at the same time (double pumping).

The device consists of a pump unit, AC power adapter, power cable, AdvancedFit flange kit and bottle kit. The AdvancedFit flange kit consists of a flange body, flange insert, check valve (valve and membrane), diaphragm, diaphragm cap, and tubing for each breast, a tubing adapter to connect the kit to the pump unit and a tubing adapter plug to convert for single pumping. It does not incorporate off-the-shelf (OTS) software or wireless technology/mobile app software functionality. The pump is powered by an internal, non-replaceable, rechargeable lithium-ion battery which is charged using the included AC power supply and cable. The subject device can be operated while plugged into AC power.

The breast pump uses cyclic negative pressure (suction) to mimic the suckling patterns of a feeding infant. A DC motor drives a membrane vacuum pump to generate the suction required to stimulate and express breast milk. The timing of this pattern is dependent upon the suction/speed settings selected by the user and is preprogrammed in the device. The device is capable of producing peak suction levels between -50 and -250 mmHg in double pumping mode and between -85 and -250 mmHg in single pumping modes at speeds between 30 and 80 cycles per minute. There are 9 distinct levels of suction and 6 speeds available for each suction level.

The breast pump expresses breast milk by creating a seal around the nipple using a flange 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 backflow protection membrane physically separates the milk-contacting pathway from the vacuum system.

All other components (i.e., motor unit) 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 the Evenflo Premium Double Electric Breast Pump (Model 4018). It focuses on demonstrating substantial equivalence to a predicate device based on similar intended use and technological characteristics, and non-clinical performance testing.

However, the document does NOT contain information about acceptance criteria for a device that uses AI/algorithm or a study involving human readers or expert consensus for ground truth establishment, which are typical for AI/ML-enabled medical devices.

Based on the provided text, I can answer some of your questions, but many will be marked as "Not applicable" or "Not provided" because the device is a breast pump, not an AI/ML diagnostic tool, and the summary focuses on equivalence to a predicate device rather than de novo performance studies as would be seen for an AI/ML device.

Here's the breakdown of the information from the document in response to your questions:

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

The document does not present acceptance criteria for AI model performance (e.g., sensitivity, specificity, AUC) or human reader performance. Instead, it describes performance testing for a breast pump, focusing on engineering specifications.

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

• Sample Size for Test Set: Not explicitly stated in terms of number of devices tested for each performance criterion. The document refers to "testing" conducted.
• Data Provenance: Not specified directly for the testing. It's implied that the testing was conducted by Evenflo Feeding, Inc. or their designated testing facilities.
• Retrospective or Prospective: Not applicable or specified for this type of device testing.

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 understood for AI/ML clinical studies (e.g., radiologist reads) is not relevant for the testing of a breast pump's mechanical and electrical performance. The "ground truth" here is the design specification or established engineering standard.

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

Not applicable. Adjudication methods are typically used in clinical studies with human readers or image analysis, not for mechanical/electrical testing of a breast pump.

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 device is a breast pump, not an AI system intended to assist human readers in, for example, diagnosing medical conditions from images.

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

Not applicable. The device does not contain an AI/ML algorithm for diagnostic purposes. Its software is for operational control (e.g., suction/speed settings).

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

Not applicable. The "ground truth" for this device's performance testing is based on engineering specifications, adherence to international standards (e.g., ISO, IEC), and functional requirements for a breast pump (e.g., vacuum levels, backflow prevention).

8. The sample size for the training set

Not applicable. This document is for a physical medical device (breast pump), not an AI/ML model that requires training data.

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

Not applicable. (See #8)

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The Electric Breast Pump is intended to express milk from lactating women in order to collect milk from their breasts.The device is intended for a single user.

Not Found

The provided text is an FDA 510(k) clearance letter for an "Electric breast pump." This document details the regulatory clearance of a physical medical device, not a software-based AI/ML device.

Therefore, the information required to answer your query – acceptance criteria, study details (sample size, data provenance, expert adjudication, MRMC, standalone performance, ground truth establishment), and training set details – is not present in the provided text.

This document is a regulatory approval for a mechanical device and does not contain the kind of performance data and study design details typically found in submissions for AI/ML-driven diagnostic or assistive technologies.

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The Momcozy Wearable Electric Breast Pump (Model: S9 Pro, S12 Pro) is a powered breast pump intended to express milk from lactating women in order to collect milk from their breasts. The device is intended for a single user.

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This document is an FDA 510(k) clearance letter for the Momcozy Wearable Electric Breast Pump. Unfortunately, it does not contain the detailed information required to answer your specific questions regarding acceptance criteria and the study that proves the device meets them.

The FDA 510(k) clearance process primarily focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, rather than requiring extensive performance studies with detailed acceptance criteria as one might see for novel AI/ML medical devices or higher-risk devices.

Here's why the document doesn't have the information you're looking for, and generally, what a 510(k) submission for a non-AI/ML device typically entails:

• Acceptance Criteria and Device Performance Table: This type of table is not part of a standard 510(k) clearance letter for a powered breast pump. A 510(k) submission might include performance testing data (e.g., motor strength, suction levels, battery life, biocompatibility), but this data is usually summarized in the submission itself, not in the clearance letter. The FDA clears the device based on the sponsor demonstrating that these performance characteristics are substantially equivalent to the predicate device, not necessarily against pre-defined clinical acceptance criteria for an AI algorithm.
• Sample Size and Data Provenance for Test Set: Not applicable in the context of this 510(k) clearance letter. There isn't a "test set" in the sense of clinical image data for an AI algorithm. Performance testing for a breast pump would involve engineering tests (e.g., measuring suction, flow rate) rather than clinical studies with patient data.
• Number of Experts, Ground Truth, Adjudication, MRMC Study, Standalone Performance: These concepts are relevant to AI/ML device evaluations. A breast pump is a mechanical device, not an AI algorithm. Therefore, none of these aspects would be part of its 510(k) submission or clearance.
• Type of Ground Truth: For a breast pump, "ground truth" would relate to its physical performance metrics (e.g., milk expression efficiency, comfort), which are assessed through engineering tests and user feedback, not expert consensus on medical images or pathology.
• Sample Size for Training Set & Ground Truth for Training Set: These are concepts specific to AI/ML model development. A breast pump does not have a "training set" in this context.

In summary, the provided document is a regulatory clearance for a medical device (a breast pump) that is not an AI/ML device. Therefore, the detailed questions about acceptance criteria, study design, and ground truth for AI model validation do not apply to this specific document or the type of device it describes.

To find the kind of information you are asking for, you would need to look at FDA clearance documents and associated summaries for AI/ML-enabled medical devices. These documents, particularly the Decision Summary (or Summary of Safety and Effectiveness), often detail the clinical study information, validation methods, acceptance criteria, and performance results for the AI algorithm.

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The Electric Breast Pumps are single-user, powered breast pumps intended to express and collect milk from the breasts of lactating women.

The subject devices are intended to be used by lactating women to express and collect milk from their breasts. The devices are intended for a single user in the home environment or hospital setting. When properly connected, the pumping kit transfers the vacuum generated by the powered pump to the breast, enabling expression and collection of milk. A diaphragm in the backflow protection assembly physically isolates pump and tubing from the space where milk is expressed and collected, protecting the breast milk from contamination.

The Electric Breast Pumps contain 4 models, YY-A203, YY-A204 and YY-TC201. The YY-A46 model operates in single pumping mode only; models YY-A203, YY-A204 and YY-TC201 can be operated in single or double pumping modes. Models YY-A203 and YY-A204 have an LED panel and model YY-TC201 has an LCD panel to display working mode, cycle, timer, battery level, and Bluetooth symbol to user. While YY-A46 has an LED indicator to indicate the working status of the device, models YY-A46, YY-A203, and YY-A204 can be wirelessly operated via Bluetooth connection to a smart device. Users can select the working mode, adjust the suction level and cycle speed, and start or pause the device from a smart device. Model YY-TC201 can only be operated on the pump unit itself. All models have massage and expression mode and have a maximum working time of 30 minutes.

The provided document is an FDA 510(k) clearance letter for Electric Breast Pumps. It details the device description, indications for use, comparison to a predicate device, and a summary of non-clinical performance testing.

However, the document does not contain information related to acceptance criteria or a study proving that the device meets those criteria, specifically concerning AI device performance. The sections discussed are typical for a breast pump's safety and performance (electrical safety, EMC, software validation, biocompatibility, vacuum/cycle performance, backflow protection, use life, battery performance) rather than AI-related metrics like accuracy, sensitivity, or specificity.

Therefore, I cannot answer the requested questions using the provided text as it does not describe an AI medical device or its performance criteria and study. The prompt asks for information pertaining to AI model validation, such as:

1. A table of acceptance criteria and reported device performance: Not present in the document for AI performance.
2. Sample size and data provenance for test set: Not present for AI device testing.
3. Number of experts and qualifications for ground truth: Not present.
4. Adjudication method: Not present.
5. MRMC comparative effectiveness study and effect size: Not present.
6. Standalone AI performance: Not present.
7. Type of ground truth used: Not present for AI evaluation.
8. Sample size for training set (AI): Not present.
9. How ground truth for training set was established (AI): Not present.

The document focuses on the hardware and basic functional performance of an electric breast pump, not an AI component.

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