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The 8-CH Electroencephalography Amplifier is intended to be used by or under the direction of a physician for acquisition of EEG signals, to transmit them digitally to a computer, and display waveform in real-time. The device is intended for use on humans. The device is intended for use in a clinical environment (e.g., hospital, physician's office, etc). The device is not intended for use in life support systems.

8-CH Electroencephalography Amplifier capture brain wave signals through non-invasive electrodes, amplify the analog signals and convert to digital signals for computer use. The EEG monitoring panel can immediately display patient's brain wave to assure signal quality of testing requirements. Begin to test when signal quality lamp on EEG monitoring panel shows green light.

The provided text is a 510(k) Summary for a medical device (8-CH Electroencephalography Amplifier). This document focuses on demonstrating substantial equivalence to an existing predicate device rather than presenting a novel device that requires extensive clinical studies to prove performance against specific acceptance criteria.

Therefore, the information typically found in a study proving a device meets acceptance criteria (like specific sensitivity/specificity thresholds, sample sizes for test sets, expert adjudication methods, MRMC studies, or standalone algorithm performance) is not present in this type of regulatory submission. The goal here is to show that the new device is as safe and effective as a device already on the market, primarily through non-clinical testing and comparison of technical specifications.

Based on the provided text, here's what can be extracted and what cannot:

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

The document states: "All the test results demonstrate 8-CH Electroencephalography Amplifier meets the requirements of its pre-defined acceptance criteria and intended use, and is substantially equivalent to the predicate device." However, the specific acceptance criteria (e.g., threshold values for electrical safety, EMC) and the numerical results for each performance test (Software Validation, Electromagnetic compatibility and electrical safety, Performance, Usability) are not detailed in this summary. The table provided (Item Feature comparison) focuses on comparing the subject device's characteristics to the predicate device, not on specific performance metrics against acceptance criteria from a study.

2. Sample sizes used for the test set and the data provenance:

• Test Set Sample Size: Not applicable/not provided. The studies mentioned (Software Validation, EMC, Performance, Usability) are non-clinical, likely involving testing of the device hardware and software, not on a dataset of patient EEG signals.
• Data Provenance: Not applicable. No clinical data was used.

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

Not applicable, as no clinical test data or data requiring expert-established ground truth was used.

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

Not applicable, as no clinical test data or data requiring adjudication was used.

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 MRMC study was done, and the device is an EEG amplifier, not an AI-driven diagnostic tool intended to assist human readers. The document explicitly states: "No clinical test data was used to support the decision of substantial equivalence."

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

Not applicable. This is a hardware device (amplifier), not an algorithm.

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

Not applicable, as no clinical data or ground truth adjudication was involved. The "ground truth" for this device's performance is compliance with engineering standards and specifications, as demonstrated through non-clinical testing.

8. The sample size for the training set:

Not applicable, as this is a hardware device undergoing non-clinical testing, not a machine learning algorithm requiring a training set.

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

Not applicable, as no training set was used.

Summary of Device Performance and Acceptance Criteria (based on available information):

• Resolution: 24 bit (Same as predicate)
• Data Storage: Yes (Same as predicate)
• Filter: Low pass filtering in amplifier (Same as predicate)
• Sampling rate: 500Hz (Same as predicate EE-430 model)
• Amplifier active shielding technique: Yes (Same as predicate)
• Amplifier CMRR (referential): 94 dB at dc to 60 Hz (Similar to predicate's >100 dB, but met IEC 60601-2-26)
• Amplifier Input Channels: 8 (Same as predicate EE-430 model)
• Amplifier input impedance (referential): >10^9 Ω (Same as predicate)
• Amplifier referential DC input channels: 8 (Same as predicate EE-430 model)
• Amplifier USB interface: Yes (Same as predicate) |
  | Usability | Tests conducted and met requirements (specifics not detailed). |
  | Clinical Testing | No clinical test data was used to support substantial equivalence. |

Study Proving Device Meets Acceptance Criteria:

The "study" is a series of non-clinical safety and performance tests. The details of these tests and their specific acceptance criteria are not provided in this 510(k) summary, but the document asserts that the device met these pre-defined criteria.

• Sample Size: Not applicable. These were likely bench tests, not data-driven studies with "samples" in the traditional sense.
• Data Provenance: Not applicable, as no clinical data was used. The device itself was tested.
• Experts/Ground Truth/Adjudication/MRMC/Standalone: Not applicable, as this is a hardware amplifier submission based on non-clinical testing and comparison to a predicate device.

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