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The device is intended to acquire, store, and transfer biophysical parameters to EEG machines for the purpose of assisting the diagnosis of neurological and sleep disorders, measurement and display of cerebral and extracerebral activity for EEG and Sleep Studies. These data, may be used by the clinician in Sleep Disorders, Epilepsies and other related disorders as a diagnostic tool. As with the predicate, the information transferred to EEG will be stored, interpreted and printed with commercially software programs available with Nihon Kohden marketed products.

The device is intended for use by medical personnel in any location within a medical facility, physician's office, laboratory, clinic or nursing home or outside of a medical facility under supervision of a medical professional. The device will be available on all patient populations, including pediatrics.

The device is intended to record, measure and display the physiological data required for EEG and sleep studies (Polysmonography or PSG). These data, may be used by clinicians in Sleep Disorders, Epilepsies and other disorders as a diagnostic aid. This device is intended for use by medical personnel and will be available for use within a medical facility or outside of a medical facility under direct supervision of a medical professional on all patient populations.

The availability of new option, CO2 Sensor and accessory provides the physician the ease of connecting the CO2 adapter directly to the amplifier instead of separately connecting to a monitor. The product design and function is equivalent to the predicate in acquisition and data development. The same sensor design is utilized in both devices. The processing unit housed within the CO2 adapter, processes data, to continously monitor non-intubated patcint's CO2. The status of real time CO2 pressure, ETCO2, expiration, and the suction point, can be transferred by the elcctrode junction box to a Nihon Kohden's EEG monitor.

The provided text describes a 510(k) submission for an Electrode Junction Box (JE-921A Series) with an added CO2 input. The document focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a study to prove the device meets specific acceptance criteria.

Therefore, many of the requested elements for describing acceptance criteria and a study cannot be directly extracted from this document, as it is a regulatory submission for device clearance based on equivalence, not a performance study report.

However, I can provide information based on what is stated:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a table of quantitative acceptance criteria for device performance (e.g., sensitivity, specificity, accuracy for a diagnostic claim) or numerically reported performance for such criteria. Instead, it states compliance with general and voluntary standards and successful completion of internal verification and validation testing.

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

The document does not describe a clinical test set or data provenance in the context of diagnostic performance or clinical accuracy. The testing mentioned refers to engineering and quality assurance tests.

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 set requiring expert ground truth establishment for a diagnostic claim is described.

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

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

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 an Electrode Junction Box and accessories, not an AI-powered diagnostic tool. There is no mention of AI or MRMC studies.

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

Not applicable, as this is hardware and does not involve a diagnostic algorithm.

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

For the internal testing described, the "ground truth" would be the engineering specifications and established standards (e.g., IEC standards, product specifications) against which the device's technical performance was measured. There is no mention of clinical ground truth like pathology or outcomes data.

8. The sample size for the training set:

Not applicable, as there is no mention of machine learning or deep learning models requiring a training set.

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

Not applicable, as there is no training set involved.

Summary of what the document does provide regarding "proof of meeting acceptance criteria":

The document primarily relies on:

• Compliance with established regulatory and voluntary standards: IEC 60601 series, 21 CFR Part 898.
• Internal verification and validation testing: This includes environmental, EMI/EMC, safety, and general performance testing, as well as software verification. The "acceptance criteria" for these tests were established based on "product specifications and applicable standards."
• Substantial Equivalence: The core argument for regulatory clearance is that the device is substantially equivalent to legally marketed predicate devices, implying similar safety and effectiveness parameters without requiring new extensive clinical performance studies. The CO2 module uses the "same sensor design" as a previously cleared module, and the overall design is "equivalent to the predicate in acquisition and data development."

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