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The Natus Quantum Amplifier is intended to be used as an electroencephalograph: to acquire, display, store and archive electrophysiological signals. The amplifier should be used in conjunction with Natus New Yorks™ software to acquire scalp and intracranial electroencephalographic (EEG) signals as well as polysomnographic (PSG) signals. The amplifier is designed to facilitate functional mapping using a Digital Switch Matrix. The Digital Switch Matrix portion of the headbox is a combination of hardware relays and software controls allowing the user (physician or technologist) to switch electrode pairs between the EEG recording amplifier and the external cortical stimulator for stimulus delivery.

The Natus Quantum Amplifier is intended to be used by trained medical professionals, and is designed for use in clinical environments such as hospital rooms, epilepsy monits, intensive care units, and operating rooms. It can be used with patients of all ages, but is not designed for fetal use.

The Natus Quantum Amplifier is the front end hardware of an electroencephalograph, and consists of amplifier circuitry, A/D Converters, Digital Signal Processing, digital switch matrix, LCD touch screen interface as well as TCP/IP & USB connection options of PC communication.

The Natus Quantum Amplifier can record either in Tethered mode or in Ambulatory Mode. In Ambulatory Mode, data is stored in the Quantum Breakout's internal memory and automatically uploaded to the main study folder when the Quantum Breakout is reconnected to the Natus Base unit.

The amplifier is designed to facilitate functional mapping using a Digital Switch Matrix. The Digital Switch Matrix portion of the headbox is a combination of hardware relays and software controls allowing the user (physician or technologist) to switch electrode pairs between the EEG recording amplifier and the external cortical stimulator for stimulus delivery by an external cortical stimulator.

The provided text describes the 510(k) summary for the Natus Quantum, an electroencephalograph (EEG) device. It primarily focuses on demonstrating substantial equivalence to a predicate device based on technical specifications, intended use, and adherence to various safety and performance standards.

However, the document does not contain information about the development and testing of a medical device that uses artificial intelligence (AI) or machine learning. Therefore, it does not provide details for the following requested information:

• A table of acceptance criteria and the reported device performance: The document lists various technical specifications (e.g., input impedance, input noise, sampling frequency) for the device and its predicate, along with general statements about compliance with standards (e.g., "Results indicate that the Natus Quantum complies with the applicable standards"). It does not outline specific acceptance criteria in the format of a table with numerical performance results directly tied to those criteria, especially not in the context of an AI/ML algorithm's performance.
• Sample size used for the test set and the data provenance: No data sets for AI/ML model testing are mentioned.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable as there's no mention of a ground truth for an AI/ML component.
• Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
• 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.
• If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
• The sample size for the training set: Not applicable.
• How the ground truth for the training set was established: Not applicable.

Summary of Device Performance (as present in the document):

The document provides a "Summary of Performance Testing" for the Natus Quantum, focusing on:

• Software: "The Natus Quantum firmware was designed and developed according to a robust software development process, and was rigorously verified and validated." It states that the firmware complies with predetermined specifications and applicable guidance documents/standards (e.g., "The content of premarket submissions for software contained in medical devices, IEC 62304: 2006").
• Electrical Safety: "The Natus Quantum was verified for performance in accordance with the following standard: IEC 60601-1: 2005, Am1: 2012." It concludes that the device "complies with the applicable standards."
• Electromagnetic Compatibility: "The Natus Quantum was verified for performance in accordance with the following standard: IEC 60601-1-2 Edition 4.0 2014-02." It concludes that the device "complies with the applicable standards."

In essence, this 510(k) pertains to a traditional medical device (an EEG amplifier) and its compliance with established electrical and software engineering standards, not the performance evaluation of an AI-powered diagnostic or assistive tool.

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The Natus Quantum Amplifier is intended to be used as an electroencephalograph: to acquire, display, store and archive electrophysiological signals. The amplifier should be used in conjunction with Natus NeuroWorks™/SleepWorks™ software to acquire scalp and intracranial electroencephalographic (EEG) signals as well as polysomnographic (PSG) signals. The amplifier is designed to facilitate functional mapping using a Digital Switch Matrix. The Digital Switch Matrix portion of the headbox is a combination of hardware relays and software controls allowing the user (physician or technologist) to switch electrode pairs between the EEG recording amplifier and the external cortical stimulator for stimulus delivery.

The Natus Quantum Amplifier is intended to be used by trained medical professionals, and is designed for use in clinical environments such as hospital rooms, epilepsy monitoring units, intensive care units, and operating rooms. It can be used with patients of all ages, but is not designed for fetal use.

The Natus Quantum amplifier is comprised of a base unit and several breakout boxes. It is part of a system that is made up of a personal computer, a photic stimulator, an isolation transformer, video and audio equipment, networking equipment, and mechanical supports. The amplifier also contains an internal switch matrix to allow for a connection to an external cortical stimulator.

EEG and other physiological signals, from scalp electrodes, grid or needle electrodes, and other accessories such as pulse oximeters can be acquired by the Natus Quantum amplifier. These signals are digitized and transmitted to the personal computer running the Natus NeuroWorks software. The signals are displayed on the personal computer and can be recorded to the computer's local storage or to remote networked storage for later review.

The provided text describes the Natus Quantum Amplifier, an electroencephalograph, and its regulatory submission (K143440). However, the document does not contain a study that directly proves the device meets specific acceptance criteria in terms of clinical performance metrics like sensitivity, specificity, or accuracy.

The document focuses on demonstrating substantial equivalence to predicate devices (EMU128S and NeuroLink IP 256) primarily through technical specifications and compliance with various safety, EMC, and quality standards. The "Performance Tests" section is very brief and refers to non-clinical verification testing rather than clinical efficacy studies.

Therefore, the following information is based on what is available or can be inferred from the provided text. Many requested fields will be marked as "Not Applicable" or "Not Provided" because the document does not describe the kind of clinical study you're asking about.

1. Table of Acceptance Criteria and Reported Device Performance

Note on Acceptance Criteria: The document implies that meeting the specified technical characteristics that are substantially equivalent or superior to the predicate devices, and passing internal design verification tests, are the "acceptance criteria" for regulatory clearance based on substantial equivalence. It does not provide clinical acceptance criteria.

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

• Sample Size: Not Applicable. The document describes non-clinical verification testing of the device hardware/software, not a clinical study on patient data.
• Data Provenance: Not Applicable. No patient data was used for the described performance tests.

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

• Number of Experts: Not Applicable. Ground truth for clinical data is not relevant to the described non-clinical verification tests.
• Qualifications of Experts: Not Applicable.

4. Adjudication method for the test set

• Adjudication Method: Not Applicable. No clinical test set requiring adjudication was 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

• MRMC Study: No. This document describes an EEG amplifier, not an AI-assisted diagnostic tool.

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

• Standalone Performance: Not Applicable. This is a hardware device (EEG amplifier) with associated software for data acquisition, display, storage, and archiving. It is not an algorithm for standalone diagnostic performance.

7. The type of ground truth used

• Type of Ground Truth: For the "Performance Tests" (Signal Quality Verification Test, Functionality Verification Test), the ground truth would be the design specifications and expected operational parameters of the device. These tests verify if the actual output matches the designed output. No clinical "ground truth" (e.g., pathology, outcomes data) for diagnosis is mentioned for these tests.

8. The sample size for the training set

• Sample Size: Not Applicable. This is not an AI/machine learning device that requires a training set.

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

• Ground Truth Establishment: Not Applicable. (See point 8)

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