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The Trackit T4 EEG Amplifier is intended to be used as a front-end amplifier to acquire, store and transmit electrophysiological signals (wireless or cabled).

The Trackit T4 EEG Amplifier is a multi-channel electroencephalograph designed for use in routine EEG and lab monitoring applications and due to its small size, can be used in ambulatory applications. In this situation, the EEG electrodes are fitted to the patient by a trained clinician prior to the patient being sent home. No subsequent intervention is required by the patient. Upon completion of the recording, the data which is stored on a memory card is reviewed by a clinician using review and analysis software on a PC. It is a compact USB amplifier which provides 32 channels with internal expansion option) with built-in calibration and electrode impedance measurement. Also provided is a Nonin pulse oximeter interface, a Patient Event input and an Aux DC input. Optional wireless communication is available (Bluetooth and WLAN WiFi). There are two variants of the Trackit T4 EEG Amplifier: - Trackit T4-32 providing 24 referential + 8 poly channels. . - . Trackit T4-68 providing 64 referential + 4 poly channels (using internal expansion board). Plug-on Patient Connection Units (PCUs) provide 32 channel touchproof inputs (model T4-PCU 24+8) or 68 channels (model T4-PCU 64+4). The Amplifier is intended to be connected to a USB port on a PC which is powered from a medically approved power supply. In addition it can be battery powered in ambulatory applications. This equipment is intended only as an adjunct device in patient assessment; it must be used in conjunction with other methods of patient diagnosis. The equipment does not sustain or support life.

This document describes the Lifelines Trackit T4 EEG Amplifier, which is substantially equivalent to the predicate device, Lifelines R-40 EEG Amplifier (K151600). The information provided is primarily focused on pre-clinical performance testing and safety, not on a study proving a device meets specific acceptance criteria based on diagnostic accuracy or clinical outcomes.

Here's an analysis of the provided text in the context of your request:

1. Table of acceptance criteria and the reported device performance:

The document primarily shows that the new device (T4) performs similarly to its predicate (R-40) in various technical tests. The "acceptance criteria" are implied by the "Test specification" and the "Conclusion" indicating "Same test as predicate" or noting the specific values the predicate device achieved.

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The R-40 EEG Amplifier is intended to be used as a front-end amplifier to acquire, store and transmit electrophysiological signals (wireless or cabled).

The R-40 EEG Amplifier is a multi-channel electroencephalograph designed for use in routine EEG and lab monitoring applications.

It is a compact USB 40-channel amplifier which incorporates 32 referential channels and 8 polygraphic channels with built-in calibration and electrode impedance measurement. A Nonin pulse oximeter interface is provided, a Patient Event input, 2 Aux DC inputs and an Electrocap connector. Optional wireless communication is available (Bluetooth and WLAN WiFi).

The Amplifier is intended to be connected to a USB port on a PC which is powered from a medically approved power supply.

This equipment is intended only as an adjunct device in patient assessment; it must be used in conjunction with other methods of patient diagnosis. The equipment does not sustain or support life.

The provided text is a 510(k) summary for the Lifelines R-40 EEG Amplifier. This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study with acceptance criteria and performance metrics in the way a clinical trial or algorithm performance study would.

Therefore, the information required to populate the table and answer the study-related questions comprehensively is not available in the provided text.

Here's why and what can be inferred:

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

• Not Available. The document states "The Lifeline R-40 EEG Amplifier meets the functional claims and intended use as described in the product labeling." and "The safety and effectiveness are substantially equivalent to the predicate device, Nicolet Wireless EEG Amplifier." However, it does not explicitly list quantitative acceptance criteria (e.g., sensitivity, specificity, accuracy, signal-to-noise ratio within a certain range) and corresponding device performance values against those criteria. The approval is based on demonstrating equivalence rather than meeting specific pre-defined performance thresholds for a novel diagnostic claim.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable/Not Available. The document explicitly states: "Clinical testing was not performed with this device." This implies there was no "test set" in the context of a clinical performance study. The evaluation was based on engineering and safety testing, and comparison of technical characteristics to the predicate device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not Applicable/Not Available. As no clinical testing was performed, there was no test set requiring ground truth established by experts.

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

• Not Applicable/Not Available. No test set or clinical data requiring adjudication.

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. This device is an EEG amplifier, not an AI-powered diagnostic algorithm designed to assist human readers. Therefore, an MRMC study related to AI assistance is not relevant or applicable here.

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

• Not Applicable. This is hardware (an EEG amplifier), not an algorithm that would be evaluated for standalone performance.

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

• Not Applicable. No clinical ground truth was established as no clinical testing was performed. The "ground truth" for this device's evaluation would be its adherence to engineering standards (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-26) and its functional specifications, which are assessed via engineering tests, not clinical ground truth.

8. The sample size for the training set

• Not Applicable. This is hardware, not a machine learning model, so there is no "training set."

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

• Not Applicable. (See point 8).

Summary of what is known from the document:

• Device Name: R-40 EEG Amplifier
• Intended Use: To acquire, store and transmit electrophysiological signals (wireless or cabled).
• Performance Evaluation Method: Primarily engineering safety testing (IEC 60601 series standards) and comparison of technical characteristics to a legally marketed predicate device (Nicolet Wireless EEG Amplifier, K103140).
• Clinical Testing: Explicitly stated as "not performed."
• Conclusion: The device meets functional claims and is substantially equivalent to the predicate device in terms of safety and effectiveness.

This type of 510(k) submission relies on demonstrating that a new device is "substantially equivalent" to an already legally marketed device, often through technical comparisons and adherence to recognized safety standards, rather than proving novel clinical performance against strict acceptance criteria in a clinical trial.

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The Lifelines Photic Stimulator is indicated for photic activation of the EEG during an EEG study and in the generation of visual evoked potentials.

The Photic Stimulator is a device for generating short-duration flashes of white light by means of a solid-state LED (light emitting diode). The flashes are controlled from a host PC and typically occur over a repetition rate of between 1 and 60Hz.

This document is a 510(k) summary for the Lifelines Photic Stimulator, which is a medical device for generating flashes of white light used in EEG studies and for generating visual evoked potentials.

The provided text does not contain a study that proves the device meets specific acceptance criteria in terms of performance metrics like sensitivity, specificity, accuracy, or other clinical outcomes. Instead, it focuses on demonstrating substantial equivalence to a predicate device (EB Neuro, S.P.A. Model BE Plus / AURA-LTM64 Amplifier) based on intended use, technological characteristics, and design.

Therefore, many of the requested sections about acceptance criteria, study details, and performance metrics cannot be directly extracted from this document as they are not present. This type of submission relies on the established safety and effectiveness of a predicate device rather than presenting new clinical performance data.

Here's an analysis based on the information available:

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

The document does not specify "acceptance criteria" in terms of performance metrics like sensitivity, specificity, or accuracy for a clinical outcome. Instead, the acceptance criteria for the 510(k) submission are based on demonstrating substantial equivalence to a predicate device. This involves matching or demonstrating comparable characteristics in:

Study Description:
The "study" presented here is a comparison to a legally marketed predicate device (EB Neuro, S.P.A. Model BE Plus / AURA-LTM64 Amplifier, K053606) to demonstrate substantial equivalence, rather than a clinical trial or performance study on humans or specialized test sets. The report asserts that the Lifelines Photic Stimulator is similar to the predicate device in intended use, technological characteristics, and design. The FDA's letter confirms substantial equivalence based on this comparison.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not applicable. This is not a study that involved a "test set" of patient data in the conventional sense. The "test" here was a comparison of device specifications and safety standards against a predicate device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. Ground truth for clinical performance was not established as there was no patient-based clinical study. The "ground truth" for the submission was the regulatory safety and performance standards met by the predicate device and the new device's adherence to relevant safety standards.

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

Not applicable. There was no clinical test set requiring adjudication.

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 a photic stimulator, not an AI-assisted diagnostic tool. No MRMC study was performed.

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

Not applicable. This device is hardware and does not involve an algorithm for standalone performance evaluation in the context of AI.

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

The "ground truth" in this context is the established safety and effectiveness profile of the predicate device, as well as adherence to relevant international and national safety standards (e.g., EN/IEC 60601-1, IEC 60825-1) for medical electrical equipment and light hazard protection.

8. The sample size for the training set

Not applicable. This device submission does not involve machine learning or a "training set."

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

Not applicable. This device submission does not involve machine learning or a "training set."

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