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The Polymap PWR-008-03 is a remote communications link intended to be used to wirelessly transmit glucose meter readings from a Blood Glucose Monitor to a compatible access point or cellular phone, such as the Nokia 6620. The device does not send any real time alarms. Clinical judgment and experience are required to check and interpret the information delivered.

The PWR-08-03 is a telemedicine device that uses Bluetooth technology to transmit data from a glucose monitor to compatible access points such as a personal computer or cellular phone with Bluetooth capability. It is connected to the glucose meter by a phono jack and uses short-range low power wireless transmission (Bluetooth VI .2) to send the data to a Bluetooth compatible access point. The unit is battery powered.

This 510(k) summary describes a remote communication link (Polymap PWR-08-03) that transmits glucose meter readings wirelessly. The submission focuses on demonstrating substantial equivalence to a predicate device rather than providing detailed performance studies or specific acceptance criteria for the device's functional performance in terms of data transmission accuracy or reliability.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not specify quantitative acceptance criteria or detailed performance metrics in the way one would typically see for diagnostic accuracy or clinical effectiveness. Instead, the "performance" discussed relates to the device's functional operation and compliance with technical standards.

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

The document mentions "bench testing" and "field testing under actual use conditions" but does not specify any sample sizes for these tests. There's no information provided regarding the data provenance (e.g., country of origin, retrospective or prospective nature).

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

This type of information is not applicable to this submission. The device is a data transmission accessory, not a diagnostic tool requiring expert interpretation of results. The "ground truth" here would relate to the accurate transmission of data, which is typically verified through technical validation rather than expert consensus.

4. Adjudication Method for the Test Set:

Not applicable. As the device is for data transmission, there's no adjudication process relevant to clinical or diagnostic outcomes.

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 communication link and does not involve AI or human interpretation of medical images or data in a way that an MRMC study would be relevant.

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

The device itself is a standalone communication module, meaning it functions without direct human interaction during data transmission. Its performance (e.g., successful data transfer, range, battery life) would have been assessed as part of the "bench testing" and "field testing" mentioned, but no specific details on these standalone tests or their metrics are provided beyond "results were acceptable."

7. The Type of Ground Truth Used:

The "ground truth" for this device would be the accurate and complete wireless transmission of glucose meter readings. This would be validated by comparing the data received at the access point/cellular phone with the original data recorded by the glucose meter. The document states "bench testing using Polymap procedures and specifications" and "field testing under actual use conditions," implying that such validation was performed, but it doesn't elaborate on the specific methodology or metrics.

8. The Sample Size for the Training Set:

Not applicable. This device is a hardware accessory for data transmission and does not utilize machine learning or AI models, therefore, there is no "training set."

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

Not applicable. (See point 8.)

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