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The Ameda GLO Wearable Breast Pump ( Model W8S ) is a powered breast pump intended to be used by lactating women to express and collect milk from their breasts. It is intended for a single user.

The Ameda GLO Wearable Breast Pump (Model W8S) is a wearable powered breast pump designed for lactating woman to express and collect milk from the breast. The device is an electrically powered, software-controlled, digital single user pump.

There are 4 modes available for the device which are Expression mode, Massage mode, Auto mode and Stimulation mode. There is a LED status display for W8S, including working mode and battery indicator can be shown on the pump body. The user interface includes on/off switch, mode selection/long press, and vacuum adjustment.

Ameda GLO Wearable Breast Pump (Model W8S) can be operated as a single or double pumping system, one on each breast. The pump is provided non-sterile and reusable by a single user. The device is powered by rechargeable Li-ion battery (3.7V, 1200mAh). W8 is designed not to be used during charging.

The breast pump does not incorporate any off-the-shelf (OTS) software. The device incorporates embedded software which controls all the features of the product. All milk contacting components of the device are compliant with 21 CFR 177 which is applicable for th subject device.

The provided document is a 510(k) summary for the Ameda GLO Wearable Breast Pump (Model W8S). It outlines the device's characteristics and compares it to a predicate device (Wearable Breast Pump, Model W8, cleared under K242850) to demonstrate substantial equivalence, rather than detailing a study that proves the device meets specific acceptance criteria for a novel functionality.

The document primarily states that performance data and testing were leveraged from the predicate device (K242850), indicating that a new, independent study for specific acceptance criteria for this particular device (Model W8S) was not conducted or detailed in this submission. Instead, confidence in the new device's performance is derived from the predicate device's established performance and the similarity in technological characteristics.

Therefore, many of the requested details such as sample size for test set, data provenance, number of experts, adjudication method, MRMC study effect size, and standalone algorithm performance are not applicable or not provided in this type of submission for this particular device, as the performance evaluation relies on the predicate device.

However, based on the provided information, I can extract the following:

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

The document does not explicitly list "acceptance criteria" in a typical quantitative sense for this device. Instead, it refers to the "Device specifications were met for all tests conducted" for performance and use life verification tests, implying the acceptance criteria are the device's specifications. These specifications are compared to the predicate device.

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

• Sample Size for Test Set: Not specified. The document states "Bench performance testing was conducted and leveraged from K242850." This implies the original testing for Model W8 (K242850) had a test set, but its details are not provided here for Model W8S.
• Data Provenance: Not specified for the leveraged data. The company is based in Shenzhen, 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 as this is a breast pump, and the criteria primarily involve engineering and material safety standards, not diagnostic interpretation requiring expert consensus.

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

• Not applicable for the types of tests described (e.g., vacuum pressure, cycle speed, material biocompatibility). These are objective measurements against defined specifications.

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-assisted diagnostic tool.

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

• Not applicable. This device is a physical medical device (breast pump) with embedded software for control, not an AI algorithm.

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

• The "ground truth" for performance is based on the device's technical specifications and compliance with recognized international standards (e.g., IEC 60601 series for electrical safety, ISO 10993 for biocompatibility) outlined by regulatory bodies. For biocompatibility, the ground truth is the biological response to materials, determined through standardized assays (cytotoxicity, sensitization, irritation).

8. The sample size for the training set

• Not applicable. This is not an AI/machine learning device that would typically have a "training set." The software is embedded control software, verified and validated against functional requirements.

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

• Not applicable, as there is no "training set" in the context of this device. Software verification and validation are typically established through testing against functional requirements, design specifications, and relevant software development lifecycle documentation rather than a "ground truth" derived from data.

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The Wearable Breast Pump (Model W8) is a powered breast pump intended to be used by lactating women to express and collect milk from their breasts. It is intended for a single user.

The Wearable Breast Pump (Model W8) is a wearable powered breast pump designed for lactating woman to express and collect milk from the breast. There are 4 modes available for the device which are Expression mode, Massage mode, Auto mode and Stimulation mode. There is a LED status display for W8, including working mode, and battery indicator can be shown on the pump body. The user interface includes on/off switch, mode selection/long press, and vacuum adjustment. W8 operated as a single or double pumping system, one on each breast. The pump is provided non-sterile and reusable by a single user. The device is powered by rechargeable Li-ion battery (3.7V, 1200mAh). W8 is designed not to be used during charging. The breast pump does not incorporate any off-the-shelf (OTS) software. The device incorporates embedded software which controls all the features of the product. All milk contacting components of the device are compliant with 21 CFR 177 which is applicable for the subject device.

Here's a breakdown of the acceptance criteria and study information based on the provided FDA 510(k) summary for the Wearable Breast Pump (Model W8).

It's important to note that the provided document is an FDA 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. It primarily details non-clinical performance testing rather than clinical efficacy studies often associated with AI/ML devices or studies directly proving therapeutic effect. Therefore, many of the requested points related to AI, human readers, ground truth establishment for patient outcomes, and clinical study designs will not be present. The "device" in this context is a physical breast pump, not an AI algorithm.

Acceptance Criteria and Reported Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

For a breast pump, "acceptance criteria" primarily relate to engineering specifications and safety standards rather than diagnostic performance metrics like sensitivity/specificity. The document states that the device was tested against its own specifications, and "Device specifications were met for all tests conducted."

The subsequent points (2-9) are typically relevant for studies involving AI/ML devices, clinical performance, or diagnostic effectiveness based on expert interpretation. As this 510(k) is for a physical medical device (a breast pump) and not an AI/ML diagnostic tool, a direct equivalent for many of these points is not applicable or explicitly mentioned in the provided summary. The summary focuses on engineering, safety, and compatibility testing.

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

• Not Applicable / Not Explicitly Stated for Clinical Outcomes: The summary describes bench performance testing on the device itself and biocompatibility testing of materials, not a clinical study on human subjects with a "test set" of patient data. For bench testing, the "sample size" would refer to the number of devices or components tested, which is not detailed but assumed to be sufficient for engineering verification.

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

• Not Applicable: This relates to human interpretation of data for ground truth establishment in diagnostic studies. For a breast pump, "ground truth" is established by engineering specifications and objective measurements (e.g., pressure gauges, timers, chemical analysis).

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

• Not Applicable: Again, this pertains to expert review and consensus for diagnostic ground truth, which is not relevant for the type of testing described here.

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-assisted diagnostic workflows. No human reader interaction or AI assistance is mentioned or relevant for a breast pump.

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

• Not Applicable: This refers to standalone AI algorithm performance. This device is a physical breast pump, not an algorithm. While it has embedded software, its performance is evaluated as an integrated system, not a standalone algorithm.

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

• The "ground truth" for this device's performance is driven by:
  • Engineering Specifications: Defined ranges for vacuum pressure, cycle speed, battery life, etc.
  • International Standards: Compliance with ISO (e.g., ISO 10993 for biocompatibility) and IEC (e.g., IEC 60601 for electrical safety and EMC) standards.
  • Regulatory Requirements: Compliance with 21 CFR regulations (e.g., 21 CFR 177 for milk-contacting materials).
  • Functional Verification: Demonstrating features like backflow protection and proper software operation.

8. The sample size for the training set

• Not Applicable: This applies to AI/ML models. This device is not an AI/ML system trained on data.

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

• Not Applicable: This applies to AI/ML models.

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