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The BE Plus LTM / GWi Amplifier is intended to be used by or under the direction of a physician for acquisition of EEG, polygraphy and polysomnography signals and transmission of these signals to a PC during recording of neurophysiology examinations.

The BE Plus LTM / GWi amplifiers system, which has 64 channels, is an amplifier system which collects the bioelectric signals from the surface of the human body trough appropriate electrodes or sensors, intensify the very low signal captured (typically the amplitude range is of the order of the uVolts), condition them (filtering), convert them in numeric form and pass these data to the "host" elaboration unit (Personal Computer or equivalent system).

For these reason this device is not intended for a "direct" use by the physician but rather by a "manufacturer" or "System Builder" (a company or a researcher) which wants to build a "complete" medical device using the "BE Plus LTM / GWi" amplifier device as the "acquiring part" of the whole system.

BE Plus LTM / GWi is therefore intended to be assembled into an electromedical system by a System Builder, who will define the specific intended use of the assembled medical device.

Here's a breakdown of the acceptance criteria and study information based on the provided 510(k) summary for the BE Plus LTM/GWi Amplifier:

1. Table of Acceptance Criteria and Reported Device Performance:

The provided 510(k) summary for the BE Plus LTM/GWi Amplifier does not present a formal table of specific acceptance criteria with quantifiable metrics. Instead, it states that:

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

• Sample Size for Test Set: The document does not specify a sample size for any "test set" in the traditional sense of a clinical trial or large-scale data evaluation. The verification and validation activities described are more aligned with engineering and software testing.
• Data Provenance: Not applicable, as there isn't a "test set" of patient data described. The testing performed was non-clinical.

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

Not applicable. This device is a physiological signal amplifier, and the testing described is primarily technical and engineering-focused (software, wireless, EMC). There is no mention of "ground truth" being established by medical experts for a clinical test set in this 510(k) summary.

4. Adjudication Method for the Test Set:

Not applicable, as no clinical test set requiring expert adjudication is mentioned.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No, an MRMC comparative effectiveness study was not done.
• Effect Size of Human Readers: Not applicable, as no such study was conducted. The device aims to acquire and transmit signals, not to provide diagnostic interpretations that would involve human readers.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

While the term "standalone" isn't explicitly used as such, the non-clinical performance data section effectively describes standalone testing of the device's technical functions and software. The device itself is described as an "acquiring part" of a larger system, indicating its primary function is data capture and transmission, not interpretation requiring a human-in-the-loop for its basic operation. The focus was on verifying its technical performance and capabilities (e.g., signal acquisition, wireless connectivity, software functionality) against predefined requirements and standards, not on its diagnostic accuracy as a standalone diagnostic tool.

7. Type of Ground Truth Used:

• For the non-clinical performance data, the "ground truth" was established by engineering specifications, functional requirements, and relevant industry standards (e.g., for software, wireless, and electromagnetic compatibility). The device's performance was compared against these established technical benchmarks.

8. Sample Size for the Training Set:

Not applicable. This device is a hardware amplifier with associated software. It is not an AI/ML algorithm that requires a "training set" of data for learning or pattern recognition.

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

Not applicable. As stated above, this device does not utilize a training set in the AI/ML context.

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