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The NeuroPort™ Array System (Neuroport Electrode) is intended for temporary (<30 days) recording and monitoring of brain electrical activity.

The NeuroPort™ Array System (Neuroport Electrode) is comprised of a base approximately 4 mm x 4 mm dimensionally with 100 microelectrodes. Each microelectrode is approximately 1 mm long. The lead connects the microelectrode array to the percutaneous pedestal connector.

The request asks for a description of acceptance criteria and the study proving the device meets those criteria, based on the provided text. However, the provided text is a 510(k) summary and FDA clearance letter for the NeuroPort™ Cortical Microelectrode Array System, largely relying on substantial equivalence to a predicate device rather than presenting a detailed clinical study with specific acceptance criteria and performance metrics for the new device.

Therefore, many of the requested sections (e.g., sample sizes, expert qualifications, adjudication methods, MRMC studies, specific performance metrics beyond biocompatibility and recording electrical activity) are not explicitly available in the provided document.

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

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

Based on the 510(k) summary, the core "acceptance criteria" are implied by the performance data, which aims to demonstrate substantial equivalence 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)

• The document mentions "non-clinical testing" as the basis for performance. It does not specify a "test set" in the context of human subjects or a clinical study for performance metrics.
• No sample size for a test set is provided.
• Data provenance (country of origin, retrospective/prospective) is not specified.

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)

• This information is not provided. The "performance data" refers to non-clinical testing rather than expert-adjudicated clinical outcomes.

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

• Not applicable/not provided, as there is no described clinical test set with human adjudication.

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

• No, an MRMC comparative effectiveness study is not mentioned. This device is a microelectrode array for recording, not an AI-based diagnostic tool for human readers.

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

• This is not an AI algorithm. The device itself is a standalone hardware product for recording brain electrical activity. The performance described relates to the device's physical and functional capabilities (biocompatibility, electrical recording), not an algorithm's performance.

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

• For biocompatibility, the ground truth would be established through biocompatibility testing standards (e.g., ISO 10993 series) which involve in-vitro and/or in-vivo animal tests to assess cytotoxicity, irritation, sensitization, etc.
• For the ability to record brain electrical activity, the ground truth would be established through bench testing and possibly animal or cadaveric studies to demonstrate stable and accurate signal acquisition, likely against known electrical signals or established physiological measurements.
• The document implies that these were evaluated against established scientific and engineering principles and recognized standards for medical device safety and performance, rather than clinical "ground truth" like pathology or expert consensus in a diagnostic context.

8. The sample size for the training set

• Not applicable/not provided. This is a hardware device, not a machine learning model requiring a training set.

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

• Not applicable/not provided.

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