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The Geodesic EEG System 400 Series™ (GES 400) is intended to measure and record the electrical activity of the patient's brain. It can be used on adults, children, and infants.

The Geodesic EEG System™ 400 Series (GES 400) is a digital electroencephalograph system (EEG). Each system consists of an amplifier, central processing unit, software, electrodes, and components of a standard personal computer (monitor, keyboard, and mouse). The GES 400 Series consists of 3 models (GES 400, GES 405, and GES 410), each of which has a slightly different amplifier. The amplifiers are very similar and all are called Net Amps ". They vary in connectors used to attach the electrodes and in the A/D chips, which support different maximum sampling rates. The other parts of the GES 400 Series are identical and consist of an isolation transformer, a power supply, Net Station software, proprietary EEG electrodes, and data acquisition computer. Optional accessories include a cart that holds the components of the system, interface cable, and articulated arm. The GES 400 Series also accepts third party DIN 42802 electrodes and an SpO22 electrode.

This 510(k) premarket notification for the Geodesic EEG System 400 Series (GES 400) primarily focuses on demonstrating substantial equivalence to its predicate device, the Geodesic EEG System 300 (GES 300), rather than outlining specific acceptance criteria or performing a clinical study to prove the device meets them in the conventional sense of a diagnostic or therapeutic AI/ML device.

The "acceptance criteria" here are implicitly related to the performance characteristics of an EEG system and demonstrating that the new device is as safe and effective as the predicate.

Here's an analysis based on the provided document:

Acceptance Criteria and Reported Device Performance

The document does not explicitly list "acceptance criteria" for the GES 400 series in terms of diagnostic accuracy, sensitivity, or specificity. Instead, the performance is demonstrated through a comparison of technical specifications against a legally marketed predicate device (GES 300). The underlying acceptance criteria are that the new device's technical specifications are comparable or improved without raising new questions of safety or effectiveness.

Study Information

The provided document describes a premarket notification for a Class II medical device, which typically relies on demonstrating substantial equivalence to a predicate device rather than conducting extensive clinical efficacy studies in the same way a novel diagnostic or therapeutic device might.

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

   • Test Set Sample Size: Not applicable. The submission states, "No animal or clinical testing was submitted." The device's performance is established through technical specification comparison and compliance with electrical safety and EMC standards, not a clinical test set with patient data.
   • Data Provenance: Not applicable. The assessment is based on engineering specifications and bench testing for electrical safety and electromagnetic interference.

2. 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 was used.

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

   • Not applicable as no clinical test set requiring adjudication was used.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

   • No, an MRMC comparative effectiveness study was not done. The device is an electroencephalograph, not a diagnostic AI intended to assist human readers in interpreting images or data.

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

   • The device itself is a data acquisition system. While it contains software (Net Station 4.5), it does not perform automated diagnoses or interpretations in a "standalone" AI sense. Its primary function is to measure and record electrical brain activity for interpretation by a human clinician. Performance assessment was based on technical specifications and adherence to relevant standards for an electroencephalograph.

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

   • Not applicable. Performance is validated through technical specification equivalence to a predicate device and compliance with electrical safety and EMC standards (UL 60601-1, IEC 60601-1-2, IEC 60601-2-26, CAN/CSA 601.1-M90, and CAN/CSA 60601-2-26). Software verification and validation (EN 62304 and EN 62366) were also conducted.

7. The sample size for the training set:

   • Not applicable. This device is an EEG system for data acquisition, not a machine learning model that requires a training set in the AI sense.

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

   • Not applicable. No training set for an AI/ML model was used.

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The Geodesic EEG Mobile 100 (GEM 100) is intended to measure and record the electrical activity of the patient's brain. It can be used on adults, children, and infants.

The Geodesic EEG Mobile 100 (GEM 100) is a digital electroencephalograph system (EEG). It consists of an amplifier, two adapters, central processing unit, software, electrodes, isolation transformer, and components of a standard personal computer (monitor, keyboard, and mouse). Integral components allow wireless communication.

The GEM 100 has 4 configurations. These are based on the type of EEG electrodes that will be used and the environment for use. The Neurotravel software is used to acquire, record, and archive the data from all 4 configurations. These configurations are:

• Ambulatory EEG only .
• Ambulatory EEG with conventional electrodes and physiological sensors ●
• Stationary (in-clinic) EEG only .
• Stationary (in-clinic) EEG with conventional electrodes and physiological sensors .

The GEM 100 EEG Amplifier is used with all configurations, but the other components vary depending on the requirements of the patient and physician. Accessories that can be used with the GEM 100 include: Sensor Kit for SpO2, LTM Net Support Kit, Video EEG, photic stimulator, TTL patient event switch, laser or inkjet printer, mobile cart, and ambulatory pouch.

The GEM 100 operates like other digital electroencephalographs. It can run on mains power or on battery power. Data can be recorded to a CompactFlash card or to the system computer. Data can be transmitted by USB connection or by Bluetooth or can be transferred from the Compact Flash card to the system computer.

This submission is for a medical device (Geodesic EEG Mobile 100), which measures and records the electrical activity of the brain. The provided text does not contain acceptance criteria for device performance, nor does it detail a study proving the device meets performance criteria. The submission focuses on substantial equivalence to a predicate device and non-clinical safety/electrical testing.

Here's a breakdown of what is and isn't present in the provided document, in relation to your request:

1. Table of Acceptance Criteria and Reported Device Performance

Not available in the provided text. The document describes the device, its intended use, and compares its features to a predicate device. It mentions "non-clinical testing" for safety and software verification/validation, but does not provide specific performance metrics or acceptance criteria for those tests.

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

Not applicable/Not available. The document explicitly states: "No clinical testing was submitted." Therefore, there is no test set of patient data, no sample size, and no data provenance information.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable/Not available. As no clinical testing was submitted, there was no need for experts to establish ground truth from patient data.

4. Adjudication Method for the Test Set

Not applicable/Not available. No clinical testing, thus no adjudication method for a test set.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Not available. The document states "No clinical testing was submitted," which means no MRMC study was conducted or provided in this submission. Therefore, there is no effect size of human reader improvement with or without AI assistance. (Note: This device is an EEG recording system, not an AI-driven diagnostic tool in the sense of image analysis, so an MRMC study comparing human reader performance on interpretations would likely be outside its scope anyway unless it involved an AI interpretation component, which is not indicated here).

6. Standalone (Algorithm Only) Performance Study

Not available. The device is an EEG recording system. Its primary function is data acquisition. While it contains software, the submission does not describe it as having a standalone "algorithm" for diagnostic interpretation or a study to evaluate its performance independently of human interpretation. "No clinical testing was submitted."

7. Type of Ground Truth Used

Not applicable/Not available. Since no clinical testing was submitted, no ground truth based on patient outcomes, pathology, or expert consensus was established for the purpose of validating the device's diagnostic performance. The device's "performance" in this submission is related to its electrical safety, software functionality, and ability to acquire EEG signals, which are assessed through engineering and non-clinical tests.

8. Sample Size for the Training Set

Not applicable/Not available. As no machine learning or AI algorithm development for diagnostic interpretation is described, there is no concept of a "training set" of patient data.

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

Not applicable/Not available. As there's no training set, there's no ground truth establishment for it.

Summary of what the document does indicate about testing:

The "Non-clinical Testing" section states:

• Extensive testing was conducted.
• The product passed general testing to IEC 60601-1, IEC 60601-1-1, IEC 60601-1-2, and IEC 60601-2-26 (international standards for medical electrical equipment safety, essential performance, and electromagnetic compatibility for electroencephalographs).
• Additional testing verified long-term monitoring capabilities and use of an SpO2 sensor.
• Software verification and validation activities were successfully completed.

These describe safety and functional performance tests against recognized standards, not clinical performance metrics or diagnostic accuracy against a ground truth from patient data.

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GeoSource is intended for use by a trained/qualified EEG technologist or physician on both adult and pediatric subjects at least 3 years of age for the visualization of human brain function by fusing a variety of EEG information with rendered images of an idealized head model and an idealized MRI image.

GeoSource is an add-on software module to EGI's Net Station software and can only be used on EEG data generated by EGI hardware. It runs on a personal computer. It is used to approximate source localization of EEG signals and visualize those estimated locations. It uses the linear inverse methods LORETA, LAURA, and sLORETA and the sphere and Finite Difference forward head models.

Here's a summary of the acceptance criteria and study details for the GeoSource device, based on the provided 510(k) notification:

Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria

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

The primary acceptance criterion for GeoSource was demonstrating substantial equivalence to predicate devices in terms of source localization accuracy. The study aimed to show that the GeoSource algorithms (LORETA, sLORETA, LAURA with FDM) provided similar source localization results to the predicate algorithm (LORETA with spherical head model).

Since this was a substantial equivalence submission, specific quantitative performance metrics and acceptance thresholds (e.g., sensitivity > X%, accuracy > Y%) are not explicitly stated in the provided text. The "reported device performance" is essentially the conclusion that the GeoSource algorithms were found to be substantially equivalent to the predicate device.

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

• Sample Size for Test Set: 20 epilepsy subjects.
• Data Provenance: Retrospective data analysis. Country of origin is not explicitly stated but implied to be from the University of Washington's Regional Epilepsy Center (USA).

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

• Number of Experts: Three.
• Qualifications of Experts: Experienced epileptologists from the University of Washington's Regional Epilepsy Center. Specific years of experience are not mentioned.

4. Adjudication method for the test set

The adjudication method involved each of the three experienced epileptologists reviewing the source localization results for each algorithm and summaries of the postoperative reports. They were then asked to rate whether each of the four algorithm solutions (GeoSource LORETA, sLORETA, LAURA with FDM, and predicate LORETA with spherical head model) were located within the resected brain regions. The text does not specify a specific consensus or majority voting method (e.g., 2+1, 3+1). It states "The results demonstrated...", implying a collective finding rather than individual expert opinions being the final ground truth.

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

• Was an MRMC comparative effectiveness study done? No, not in the typical sense of evaluating human reader performance with and without AI assistance. This study focused on the performance of the algorithms themselves by having experts evaluate the algorithm's outputs in relation to the ground truth. It did not directly measure how much human readers improved by using the GeoSource software.

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

• Was a standalone study done? Yes, in essence. The study's primary goal was to evaluate the GeoSource algorithms' source localization accuracy in a standalone manner, with expert epileptologists providing the "ground truth" assessment of whether the algorithm's output correlated with the resected region. The experts were evaluating the algorithms' predictions, not using the algorithm as assistance for their own interpretation.

7. The type of ground truth used

• Type of Ground Truth: A combination of clinical and outcome data:
  • Clinical Neurophysiologist review: Identification and averaging of spikes in EEG data.
  • Operative data: Descriptions of the resected zone from surgery.
  • Outcomes Data: Postoperative Engel 1 or 2 determination (indicating good seizure control after resection).
  • Expert Consensus/Evaluation: The decision of three experienced epileptologists on whether the source localization algorithm's output was within the resected brain regions, using all available clinical information (postoperative reports, resected zone descriptions) as context.

8. The sample size for the training set

The document does not provide information about a separate "training set" for the GeoSource algorithms. The mentioned clinical study was a retrospective data analysis of subjects who had previously undergone resection surgery, and this data was used to test the algorithms' performance, not to train them. Source localization algorithms like LORETA, sLORETA, and LAURA are typically model-based and do not require a separate "training set" in the same way machine learning models do.

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

As no specific training set is identified for the GeoSource algorithms, the question of how its ground truth was established is not applicable in the context of this 510(k) submission. These linear inverse methods are derived from mathematical and biophysical principles rather than being "trained" on a dataset with a predefined ground truth.

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