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510(k) Data Aggregation
(190 days)
Wearable Breast Pump (Model W6)
The Wearable Breast Pump (Model W6), 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 W6) is a powered breast pump intended to be used by lactating women to express and collect milk from their breasts; they are intended for a single user. Wearable Breast Pump (Model W6) is a breast pump powered by lithium battery, utilizing an embedded control program to manage all device functions. The main components of this pump includes: Pump, valve, control board, and milk collector. The user interface allows the user to switch from stimulation, expression, auto, and hot compress modes and control the vacuum levels within those modes.
The Wearable Breast Pump (Model W6) is capable of providing 12 vacuum levels from 40-120 mmHg with cycling rates from 90-143 cycles per minute in stimulation mode, vacuum levels from 105-245 mmHg with cycling rates from 30-105 cycles per minute in expression mode, vacuum levels from 40-150 mmHg with cycling rates from 87-128 cycles per minute in massage mode, and vacuum levels from 40-245 mmHg with cycling rates from 30-143 cycles per minute in auto mode. The Wearable Breast Pump (Model W6) has a hot compress mode with one heating level
This FDA 510(k) clearance letter pertains to a Wearable Breast Pump (Model W6), not an AI/software device that requires acceptance criteria for algorithm performance. The acceptance criteria and study detailed in the provided text are focused on the hardware performance, safety, and functionality of a physical medical device (a breast pump), not the diagnostic or analytical performance of an AI model.
Therefore, many of the requested items related to AI model evaluation (like sample size for test/training sets, data provenance, expert ground truth, MRMC studies, standalone performance, etc.) are not applicable to this document.
However, I can extract the acceptance criteria and the studies performed to prove the device meets these criteria as described in the 510(k) summary, reframing them to fit the provided sections where possible.
Acceptance Criteria and Device Performance for Wearable Breast Pump (Model W6)
Given that this document describes a physical medical device (a breast pump) and not an AI/software for diagnosis or analysis, the acceptance criteria and performance studies are focused on the device's functional safety and efficacy.
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria Category | Specific Acceptance Criteria (as implied or stated) | Reported Device Performance (from "Summary of Non-Clinical Performance Testing") |
---|---|---|
Biocompatibility | Compliance with ISO 10993-1 for patient contact materials. | Leveraged from predicate device; in accordance with 2023 FDA guidance. Implies successful demonstration of biocompatibility. |
Electrical Safety | Compliance with IEC 60601-1 Ed 3.2, IEC 62133-2:2017, and IEC 60601-1-11 Ed 3.1. | Testing conducted successfully. Implies successful demonstration of electrical safety. |
Electromagnetic Compatibility (EMC) | Compliance with IEC 60601-1-2:2014+A1:2020. | Testing conducted successfully. Implies successful demonstration of electromagnetic compatibility. |
Software Functionality | Software functions as intended and meets "Basic Documentation level" requirements per FDA guidance. | Evaluated at the Basic Documentation level successfully. Implies successful verification of software functionality. |
Vacuum Level Verification | Devices meet specified vacuum ranges (±5 mmHg) for each mode. |
- Stimulation: 40-120 mmHg
- Expression: 105-245 mmHg
- Massage: 40-150 mmHg
- Auto: 40-245 mmHg | Demonstrated that the devices meet mode/cycle specifications. Implies successful verification that actual vacuum levels fall within the stated ranges. |
| Cycle Speed Verification | Devices meet specified cycling rates (±2 cycles/minute) for each mode. - Stimulation: 90-143 cycles/min
- Expression: 30-105 cycles/min
- Massage: 87-128 cycles/min
- Auto: 30-143 cycles/min | Demonstrated that the devices meet mode/cycle specifications. Implies successful verification that actual cycle speeds fall within the stated ranges. |
| Backflow Protection | Liquid does not backflow into the tubing. | Testing verified liquid does not backflow into the tubing. Implies successful backflow protection. |
| Use Life Consistency | Devices maintain specifications throughout their proposed use life. | Testing conducted to demonstrate devices maintain specifications. Implies successful use life performance. |
| Battery Performance | Battery remains functional during its stated battery use-life. | Testing conducted to demonstrate battery remains functional. Implies successful battery performance. |
| Battery Status Indicator Functionality | Battery status indicator remains functional during its stated battery life. | Testing conducted to demonstrate indicator remains functional. Implies successful battery status indicator performance. |
| Hot Compress Temperature | Hot compress function remains functional during stated use-life and provides a heating level ≤ 42 ºC. | Testing conducted to demonstrate hot compress function remains functional. Implies successful temperature control (≤ 42 ºC) and functionality throughout use-life. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: The document does not specify exact sample sizes for each performance test (e.g., number of units tested for vacuum, cycle speed, use-life, etc.). It only states that "testing was conducted."
- Data Provenance: Not specified in terms of country of origin or whether the underlying studies were retrospective or prospective. These are typically laboratory performance tests, not clinical data.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
- Not applicable. This relates to evaluation of AI/diagnostic algorithms. For a physical device like a breast pump, "ground truth" is established by direct measurement against engineering specifications and industry standards, not by expert human graders of images or clinical data.
4. Adjudication Method for the Test Set
- Not applicable. This relates to resolving discrepancies in expert labeling for AI/diagnostic algorithms. For device performance testing, adjudication is generally a process of reviewing test results against predefined engineering limits and specifications, not expert consensus on qualitative data.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done
- No, not specified and not applicable. An MRMC study is relevant for evaluating the impact of AI assistance on human performance in diagnostic tasks. This document describes the performance of a physical breast pump.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done
- Not applicable for the overall device performance in the context of typical AI review. While the breast pump does have "embedded software," the performance described (vacuum, cycle speed, battery, etc.) is the device's standalone performance, not an algorithm's diagnostic or analytical performance. The document states "Software was evaluated at the Basic Documentation level," which refers to standard software validation processes for medical devices, not an "algorithm-only" performance study in the AI sense.
7. The Type of Ground Truth Used
- Engineering Specifications and Standardized Test Methods: The "ground truth" for this device's performance is derived from established international standards (IEC 60601 series, ISO 10993-1) and the device's own design specifications (e.g., specific vacuum ranges, cycle speeds, temperature limits). These are objective, measurable criteria. For example, a vacuum gauge provides the "ground truth" for vacuum level, and a timer/counter for cycle speed.
8. The Sample Size for the Training Set
- Not applicable. This device does not use a "training set" in the context of machine learning. Its internal software is "embedded" and controls device functions based on pre-programmed logic, not learned from data.
9. How the Ground Truth for the Training Set was Established
- Not applicable. (See point 8).
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