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The XLTEK EMU40EX EEG Headbox is an electroencephalograph that works in conjunction with XLTEK NeuroWorks software.

The XLTEK EMU40EX EEG Headbox is used to acquire, digitize, store and transmit physiological signals (such as EEG, pulse and oximetry signals) for EEG studies in research and clinical environments.

The XLTEK EMU40EX EEG Headbox requires competent user input, and its output must be reviewed and interpreted by trained medical professionals who will exercise professional judgment in using this information.

The Natus Medical Incorporated DBA Excel-Tech Ltd. (XLTEK) EMU40EX System is a powerful and flexible EEG recording system. The EMU40EX System consists of a patient electrode set, EMU40EX EEG Headbox, and the Natus Base Unit.

The EMU40EX System is designed to work with an XLTEK host computer system running the Natus Database and Natus NeuroWorks® data review and analysis software.

The EMU40EX EEG Headbox can be connected to the Natus Base Unit with a cable, or can connect wirelessly through a secure BlueTooth link

The provided document is a 510(k) premarket notification for a medical device called the XLTEK EMU40EX EEG Headbox. This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving novel effectiveness or performance through typical clinical studies with specific acceptance criteria in the way a new drug or high-risk medical device might.

Here's an analysis based on the information provided, keeping in mind the context of a 510(k) submission:

1. Table of Acceptance Criteria and Reported Device Performance

Explanation of the Study and Device Meeting Acceptance Criteria:

The "study" described here is a set of engineering and performance verification and validation tests, not a clinical trial in the traditional sense. The device, an EEG headbox, is a Class II medical device, and the submission is a 510(k), which seeks to demonstrate "substantial equivalence" to a legally marketed predicate device (XLTEK EMU40 EEG Headbox, K053386).

The acceptance criteria are therefore largely derived from recognized international standards for medical electrical equipment, software development, and specific performance attributes expected of an EEG headbox. The device is deemed to meet these criteria by successfully passing the various verification and validation tests outlined in the document.

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

• Test Set Sample Size: Not applicable in the context of this engineering-focused 510(k) submission. There is no "test set" of patient data or clinical cases described for evaluating algorithm performance. The testing involved hardware, software, and system-level performance against engineering standards.
• Data Provenance: Not applicable. The "data" refers to test results from in-house engineering and laboratory testing, rather than patient data.

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

• Number of Experts: Not applicable. Ground truth, in the sense of clinical interpretations or diagnoses for a dataset, is not part of this type of submission for this device. The "ground truth" for the engineering tests would be the established international standards and their specified parameters (e.g., a certain level of electromagnetic compatibility, signal fidelity characteristics, etc.), which are not established by individual experts for each test. Internal engineering and quality assurance personnel would verify adherence to these standards.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable for the reasons outlined in point 3. Testing involves objective measurements against predefined engineering specifications.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Improvement with AI vs. Without AI Assistance

• MRMC Study: No, an MRMC comparative effectiveness study was not done.
• Effect Size of Human Improvement with AI: Not applicable. This device is an EEG headbox, a signal acquisition and digitization component. It is not an AI-powered diagnostic or interpretive algorithm designed to assist human readers. It acquires physiological signals for interpretation by trained medical professionals using other software (XLTEK NeuroWorks software), but the headbox itself does not have AI capabilities that would directly improve human reader performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop) Performance Study Was Done

• Standalone Performance Study: No, this device is not an algorithm that performs standalone diagnoses or interpretations. It is hardware that acquires data. Its performance is evaluated based on its ability to accurately and safely acquire and transmit physiological signals, not on diagnostic accuracy.

7. The Type of Ground Truth Used

• Type of Ground Truth: For this device, the "ground truth" for its performance is adherence to established engineering standards (e.g., IEC 60601 series, ISO 80601 series) and the manufacturer's internal product specifications for signal quality, functionality, usability, and safety. There is no clinical "ground truth" (like pathology, expert consensus on images, or outcomes data) involved for this hardware component.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device does not use machine learning or AI algorithms that require a "training set" of data for development. Its firmware design and development follow a robust software development process, but this is traditional software engineering, not machine learning.

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

• Ground Truth for Training Set: Not applicable, as there is no training set for this device.

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