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The Lifelines iEEG is an EEG system that allows acquisition, display, archive, storage and analysis of physiological signals. The intended user of this product is a qualified medical practitioner trained in electroencephalography who will exercise professional judgment in using the information. The Lifelines iEEG system also includes the display of a quantitative EEG plots, power spectrum, which is intended to help the user to monitor and analyze the EEG. This device does not provide any diagnostic conclusion about the patient's condition to the user.

Lifelines iEEG is medical device used to acquire, display, archive, store and analyze EEG examinations. The EEG is presented in a conventional way and conventional signal processing is applied such as re-montaging and band pass filtering. The system is also capable of acquiring and presenting digital video synchronized to the EEG if this is available. Some advanced analysis methods are provided as an aid: FFT analysis and Artifact Removal. The system software is designed using service oriented architecture enabling the possibility of reviewing data over WAN without the use of additional remote desktop software solutions.

The components of Lifelines iEEG are:

• Lifelines iEEG software:
  • . iEEG Centrum
  • . iEEG Review
  • iEEG Acquisition .
• Lifelines Trackit, Lifelines Ltd, 510(k)#K010460
• Lifelines Photic Stimulator, Lifelines Ltd, 510(k)# K101691 ●
• Off the shelf PC and medical grade power supply ●
• Off the shelf IP Video Camera ●

This 510(k) submission for the Lifelines iEEG 2.0 device primarily focuses on demonstrating substantial equivalence to a predicate device (Natus Medical, Inc., DG Nervus/NicoletOne, K964280) rather than presenting a standalone study with acceptance criteria for clinical performance. The documentation emphasizes software verification and validation, along with conformance to various IEC standards for safety and essential performance.

Therefore, many of the requested sections related to clinical study design, sample sizes for test/training sets, expert adjudication, MRMC studies, and ground truth establishment are not explicitly addressed in this document. The device is an EEG system for acquisition, display, archive, storage, and analysis of physiological signals, and the submission argues that it is substantially equivalent to existing, legally marketed devices.

Here's a breakdown of the available information:

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

No explicit acceptance criteria or reported device performance metrics in terms of clinical accuracy (e.g., sensitivity, specificity for diagnostic tasks) are provided in this document. The submission focuses on demonstrating substantial equivalence based on intended use, technological characteristics, and conformance to safety and performance standards.

The document highlights the following characteristics of the Subject Device (Lifelines iEEG):

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

This information is not provided in the document. The submission details non-clinical performance data, primarily software verification and validation, and conformance to electrical safety and EMC standards. There is no mention of a test set derived from patient data for evaluating clinical performance.

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)

This information is not provided as there is no described clinical test set or ground truth establishment based on expert consensus for clinical performance.

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

This information is not provided as there is no described clinical test set or adjudication process for clinical performance.

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 comparative effectiveness study was done regarding the Lifelines iEEG device improving human reader performance. The device is an EEG system for acquisition and analysis, not an AI-assisted diagnostic tool that interprets EEG data for the user. Its quantitative EEG plots (power spectrum) are intended to help the user monitor and analyze the EEG, but it explicitly states: "This device does not provide any diagnostic conclusion about the patient's condition to the user."

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

No standalone performance study (in a diagnostic sense) was conducted or reported. The device's primary function is to acquire, display, and provide tools for analysis to a human expert, not to perform independent diagnostic interpretations. The document states it "does not provide any diagnostic conclusion." The non-clinical performance data focuses on the technical aspects of the software and hardware components.

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

Not applicable for clinical performance evaluation as described in this document. The "ground truth" in the context of the reported non-clinical performance data would be the expected behavior of the software and hardware according to its design specifications and relevant international standards.

8. The sample size for the training set

This information is not provided. The device is an EEG acquisition and analysis system, not a machine learning model that would typically have a distinct "training set" of clinical data for learning diagnostic patterns.

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

This information is not provided as there is no described training set for a machine learning model with established ground truth.

Summary of Device and Performance Context:

The Lifelines iEEG 2.0 is an electroencephalograph (EEG) system intended for qualified medical practitioners trained in electroencephalography. It allows for the acquisition, display, archive, storage, and analysis of physiological signals, including quantitative EEG plots (power spectrum).

The submission argues for substantial equivalence to the predicate device (DG Nervus/NicoletOne) by detailing similarities in intended use, users, population, use environment, regulation, and core principles of operation (signal processing, montage, filtering, data plotting).

The main differences noted are:

• Lifelines iEEG does not offer automated spike and seizure detection, which the predicate device does. The applicant argues these are "nice-to-have features that are not essential to an EEG system."
• Lifelines iEEG supports fewer EEG channels (up to 128 software, 32 hardware) compared to the predicate (up to 512).
• Lifelines iEEG includes the OLT product code for quantitative EEG, and supports its own proprietary (.ieeg) recording type.
• Lifelines iEEG includes wireless communication and video camera support as added features not present in the predicate.
• Minor differences in channel equivalent input noise, frequency band, filter ranges, and sampling rates between the subject and predicate device.

The "study" described is primarily a non-clinical performance evaluation consisting of:

• Software Verification and Validation
• Immunity Verification
• Third-party testing for conformance with IEC 60601-1:2005 (basic safety and essential performance)
• Third-party testing for conformance with IEC 60601-1-2:2007 (electromagnetic compatibility)
• Checklist testing for IEC 62304:2006 (Medical Device Software Life Cycle Processes)
• Checklist testing for IEC 62366:2007 (Usability Engineering)
• Third-party testing for conformance with IEC 60601-2-26:2002 (Particular requirements for the safety of electroencephalographs)

The absence of clinical performance data and acceptance criteria for diagnostic accuracy is consistent with the device's stated indications for use, which explicitly state it "does not provide any diagnostic conclusion about the patient's condition to the user." Its primary role is as a tool to aid qualified practitioners in their analysis.

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The Lifelines iEEG is a software system that displays physiological signals. The intended user of this product is a qualified medical practitioner trained in Electroencephalography. This device is intended to be used by qualified medical practitioners who will exercise professional judgment in using the information.

• The Lifelines iEEG software allows display, archive, review and analysis of . physiological signals.
• Lifelines iEEG also includes the display of a quantitative EEG plot, power . spectrum, which is intended to help the user to monitor and analyze the EEG.
  This device does not provide any diagnostic conclusion about the patient's condition to the user.

Lifelines iEEG is software system used to manage and review EEG examinations. It works on data acquired by third party EEG equipment that is imported into the system. The EEG is presented in a conventional way and conventional signal processing is applied such as re-montaging and band pass filtering. The system is also capable of presenting digital video synchronized to the EEG if this is available. Some advanced analysis methods are provided as an aid: FFT analysis and Artifact Removal.
The software is designed using service oriented architecture enabling the possibility of reviewing data over WAN without the use of additional remote desktop software solutions. The two main components of Lifelines iEEG are iEEG Centrum and iEEG Review.

Here's an analysis of the provided text regarding the acceptance criteria and study information for the Lifelines iEEG device:

Based on the provided K123665 510(k) Summary, the Lifelines iEEG is a software system for managing and reviewing EEG examinations. It displays physiological signals and provides analysis features like FFT and Artifact Removal. Crucially, the document does not detail specific acceptance criteria or a study proving that the device meets such criteria in terms of clinical performance or accuracy thresholds. Instead, the submission focuses on demonstrating substantial equivalence to predicate devices based on functional similarities and safety considerations.

The device does not provide any diagnostic conclusion and is intended for use by qualified medical practitioners who will exercise professional judgment. This implies that the software acts as a tool for presentation and analysis, rather than a diagnostic algorithm requiring performance metrics like sensitivity, specificity, or AUC.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not describe a specific test set with a defined sample size for evaluating the clinical performance of the Lifelines iEEG in terms of diagnostic accuracy or other performance metrics. The comparison is primarily functional.

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

Since there is no described test set for clinical performance evaluation, there's no mention of experts establishing ground truth for such a set.

4. Adjudication Method for the Test Set

As there is no described test set requiring a ground truth, there is no adjudication method mentioned.

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

An MRMC study was not conducted or described in this 510(k) summary. The device's purpose is not to assist human readers in a diagnostic task that would be directly compared to unassisted reading, as it doesn't provide diagnostic conclusions or AI-driven interpretations beyond basic signal processing.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The document does not describe any standalone performance study in terms of diagnostic effectiveness for the algorithm itself. The device is a software system intended to be used by a qualified medical practitioner.

7. The Type of Ground Truth Used

Given the lack of a clinical performance study with acceptance criteria, no specific type of ground truth (e.g., expert consensus, pathology, outcomes data) is mentioned as being used for performance evaluation.

8. The Sample Size for the Training Set

The document does not mention a training set or any deep learning/machine learning models that would require one. The functions described (re-montaging, band pass filtering, FFT analysis, Artifact Removal) are conventional signal processing techniques, not typically "trained" on data in the way AI algorithms are.

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

As no training set is described, this information is not applicable and not provided.

Summary of Device Evaluation Approach:

The K123665 submission for Lifelines iEEG primarily relies on demonstrating substantial equivalence to predicate devices based on functional characteristics and safety considerations stemming from standard signal processing methods. The key argument is that the Lifelines iEEG performs similar functions (display, archive, review, analysis of EEG signals) to the predicate devices, despite lacking the acquisition and specific spike/seizure detection functionalities. The safety and effectiveness are inferred from the use of conventional, industry-standard methods for signal processing, which are assumed to be similar enough to predicate devices such that the device does not raise new questions of safety or effectiveness. No specific clinical performance metrics or studies proving diagnostic accuracy are presented because the device's intended use is as a display and analysis tool, not a diagnostic aid providing conclusions.

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