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The Flexset system is intended for prescription use in a healthcare facility, home, and specific transport environments to acquire, transmit, display and store EEG and auxiliary signals for adults and children, not including newborns. The Flexset system acquires, transmits, displays and stores electroencephalogram (EEG), and optionally electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), orientation sensor data, photic sensor data, external trigger signals and video.

The Flexset System is intended to acquire, transmit, display and store primarily EEG and optionally auxiliary signals. Specific transport environments in the Indications for Use include ambulances, cars, buses, trains, boats and via air, per stipulation in the user manual of the device. The Flexset headset is designed to record a full montage EEG, with optional external references and additionally up to 8 auxiliary channels using lead wires for EEG, EOG, ECG or EMG. The device consists of the following components:

• Flexset (Headset) .
• Electrodes
• Charger with cable ●
• Display Unit ●
• Extension Unit ●
• Lead wires ●
• Software ●
  • Display Unit firmware o
  • Data center application (same as K172735) O
  • O Client application (same as K172735)

The provided 510(k) summary for the Zeto, Inc. Flexset System does not contain the specific details about the acceptance criteria or a dedicated study proving the device meets those criteria in the way typically expected for an AI/ML-driven diagnostic device.

This document describes a device for acquiring, transmitting, displaying, and storing EEG and auxiliary signals. It focuses on demonstrating substantial equivalence to a predicate device (WR19 System) and a secondary predicate device (X-Series System) based on technological characteristics and intended use. The performance data section refers to compliance with general medical device standards (e.g., IEC 80601-2-26:2019 for EEG performance) rather than specific acceptance criteria for diagnostic performance outcomes.

Therefore, many of the requested items cannot be extracted directly from this document. However, I can infer some information based on the provided text.

Here's a breakdown of what can and cannot be answered:

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

Limitations: The document does not specify quantitative acceptance criteria (e.g., "EEG noise must be

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The Neuronaute Plus is a system intended to acquire, store, archive, and periodically transmit physiological signals from the brain using a full montage array to enable review at a physician's office, hospital, or other remote locations. It allows remote access by users via the BioSerenity Cloud.

The Neuronaute Plus and its associated software are intended to assist in the diagnosis of neurological disorders. The Neuronaute Plus and its components do not provide any diagnostic conclusions or automated alerts of an adverse clinical event about a patient's clinical condition.

The Neuronaute Plus is intended to be used by trained healthcare professionals, technicians or patients above 15 years old. In case of a patient below 15 years old, Neuronaute Plus is intended to be used by a care giver.

Adequate training is recommended for proper use of the device.

Neuronaute IceCap 2 electrodes are able to be used on patients weighing at least 10 kg and having a head circumference above 43 cm.

Neuronaute is not intended to replace direct communication with healthcare providers. The system data should not be used alone, but should be used along with all other clinical data and exams to come to a diagnosis.

The BioSerenity Cloud allows the display of signals in the diagnosis of physiological disorders through the data collected by recording.

The BioSerenity Cloud should allow the analysis and filtering of data in order to aid doctors in diagnosing neurological disorders.

The Neuronaute Plus is a non-invasive medical device which enables the acquisition, recording, storage and transmission of electrophysiological signals in order to analyze potential neurological disorders.

The system is composed of the pieces of equipment listed below, and the Neuronaute Plus components are connected through Bluetooth and Wi-Fi.

• -Neuronaute Plus (Core module): is a signal acquisition system: an electronical amplifier that records EEG, ECG, EMG, EOG and breathing signals via a connection to EEG caps which transmits the data to the Neuronaute mobile application and Cloud system.
• -Neuronaute Plus IceCap extender : is a removable interface to connect the signal acquisition system to the IceCap and IceCap2 & 2 Small.
• -Neuronaute Plus DB25 Extender : is a removable interface that can connect the signal acquisition system to any DB25-compatible EEG cap.
• -Holding band : is a wearable textile band which allows the patient to place the Neuronaute Plus close around his chest over clothes. the use of the holding band is optional.
• -Neuronaute IceCap: is a single use 21 electrode headset that connects to the Neuronaute Head Module via the IceAdapter, the DB25 cable and the Neuronaute BioAdapter, or Neuronaute Plus with its IceCap Extender. Recently, the Neuronaute Touchproof Adapter was developed to connect the IceCap electrode to Neuronaute Head module via a touchproof channel.
• Neuronaute IceCap 2 & 2 Small: recently cleared version of the IceCap dedicated to adults and pediatric patients. It connects similarly to Neuronaute and Neuronaute Plus.
• Neuronaute Mobile APP: is compatible with iOS systems. The mobile application enables the healthcare professionals to access and manage the prescribed recording sessions.
• -Bioserenity CLOUD: is a web-based information system that receives the EEG signals from the recorder through a paired Wi-Fi connection. The cloud platform enables long-term storage and display of the recorded signals. The physician, who prescribes the use of this device, should monitor its use and confirm the proper functioning of signal recording through the Neuronaute Cloud.
• -VEEG pack: it is composed of the Neuronaute N-DEO and Neuronaute N-WAY. The Neuronaute N- DEO camera enables the visualization of the patient during a recording. The IP camera provides HD resolution video sequence at 1080p, with advanced night mode and WDR technology. The Neuronaute N- WAY enables wireless connectivity (4G) for remote monitoring and data transmission to the cloud platform.

The provided text does not contain the detailed information required to fill out a table of acceptance criteria and reported device performance for a diagnostic device, nor does it describe a study that proves the device meets specific performance criteria for diagnosis with quantitative metrics like sensitivity, specificity, or accuracy.

The document is a 510(k) Premarket Notification for the Neuronaute Plus, which establishes its substantial equivalence to an existing predicate device (Neuronaute). This clearance pathway primarily focuses on demonstrating that the new device is as safe and effective as a legally marketed device, rather than proving its diagnostic performance against specific, quantitative acceptance criteria in a clinical study.

Here's why the requested information is largely absent and what the document does provide:

1. Acceptance Criteria and Reported Device Performance (Table):

   • The document lists several non-clinical tests (electrical safety, EMC, wireless safety, PEMS, cybersecurity, biocompatibility, usability, battery safety) that the Neuronaute Plus underwent.
   • For each of these, the "acceptance criterion" is implicitly "passed" or "fulfills the requirements of the standard."
   • The "reported device performance" is simply that "all tests... are in passed status" or "the product fulfills the requirements of the standard."
   • Crucially, there are no diagnostic performance metrics (e.g., sensitivity, specificity, AUC) or corresponding acceptance criteria because the device is an EEG acquisition and display system, not an AI diagnostic algorithm that provides conclusions or automated alerts. Its "performance" is primarily about its ability to accurately acquire and display physiological signals safely and effectively, comparable to its predicate.

   Therefore, a table of acceptance criteria and reported device performance related to diagnostic accuracy (as typically seen for AI/ML devices) cannot be constructed from this document. The performance testing described is focused on safety, electrical compatibility, and usability compared to a predicate device.

   Conceptual Table (based on safety/functional tests, not diagnostic accuracy):

   Area of Test	Acceptance Criteria	Reported Device Performance
   Electrical Safety	Compliance w/IEC 60601-1, -11, -26	All tests passed; substantially equivalent to predicate.
   EMC Tests	Compliance w/IEC 60601-1-2	All tests passed; fulfills requirements of standard.
   Wireless Safety	Radio-emission safety	All tests passed; substantially equivalent to predicate.
   PEMS (Firmware)	Software safety & electrical perf.	All tests passed.
   Cybersecurity	Meets FDA guidance	Design process demonstrates safety; post-market plan.
   Biocompatibility	Compliance w/ISO 10993-1, FDA guid.	No further testing required; classified as biocompatible.
   Usability	No critical/major use errors	Validation criteria met; no critical/major use errors.
   Battery Safety	Compliance w/IEC 62133, 60601-1	All tests passed.

2. Sample Size and Data Provenance for Test Set:

   • Diagnosis/AI Performance Test Set: Not applicable. The document explicitly states: "No clinical data was needed for demonstrating substantial equivalence of the Neuronaute Plus."
   • Usability Study Test Set:
     • Sample Size:
       • User group 1 (Healthcare professionals): n=9 (Physicians, nurses, technicians)
       • User group 2 (Patients): n=15 (aged 15-30, 31-50, >50 years)
     • Data Provenance: Not specified, but generally, human factors/usability studies are prospective and often conducted in a simulated environment by the manufacturer. Country of origin is not mentioned.

3. Number of Experts and Qualifications for Ground Truth:

   • Not applicable for diagnostic ground truth as no clinical diagnostic performance study was conducted.
   • For the usability study, "trained healthcare professionals" were part of the user group, but their role was as study participants, not as ground truth experts for a diagnostic outcome.

4. Adjudication Method for Test Set:

   • Not applicable for a diagnostic test set, as no such test was conducted.
   • For the usability study, the "validation criteria are met," and "no use errors leading to critical or major risks... occurred." This implies an assessment against predefined usability metrics, likely by study administrators, but no details on an adjudication panel for "ground truth" are provided.

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

   • No. This study type is typically for assessing human reader performance with and without AI assistance for diagnostic interpretation. The Neuronaute Plus is an EEG acquisition and display system, not an AI interpretive algorithm. Its purpose is to assist in diagnosis by providing signals for a healthcare professional to review, not to provide diagnostic conclusions itself.
   • The Indications for Use clearly state: "The Neuronaute Plus and its components do not provide any diagnostic conclusions or automated alerts of an adverse clinical event about a patient's clinical condition."

6. Standalone (Algorithm Only) Performance:

   • Not applicable. The Neuronaute Plus is a hardware system with associated software for signal acquisition, storage, and display. It does not contain a standalone diagnostic algorithm that produces a diagnostic output without human intervention.

7. Type of Ground Truth Used:

   • For diagnostic purposes, none was used or required, as per the 510(k) clearance process for this type of device (EEG acquisition/display).
   • For non-clinical tests (electrical safety, EMC, etc.), the "ground truth" is adherence to established consensus standards (e.g., IEC standards).

8. Sample Size for Training Set:

   • Not applicable. There's no mention of an AI/ML component that requires a training set for diagnostic classification or prediction. The device's software handles data acquisition, storage, transmission, and display, which are typically validated through verification and validation testing against functional requirements and standards, not through training data.

9. How Ground Truth for Training Set was Established:

   • Not applicable, as no training set for an AI/ML diagnostic algorithm is mentioned.

In summary: The provided document is a 510(k) clearance letter for an EEG acquisition and display system (Neuronaute Plus). Its "acceptance criteria" and "proof" primarily revolve around demonstrating safety, functional performance, and substantial equivalence to a predicate device through non-clinical testing and usability studies, rather than clinical diagnostic accuracy studies common for AI-powered diagnostic aids.

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The NeuroField Q21 System is indicated for prescription use to acquire, record, transmit, and display physiological data for electroencephalographic (EEG) studies of patients of all ages.

The Q21 is a 20-Channel Quantitative Electroencephalogram (QEEG) system which records 24-bit high resolution EEG data. NeuroField EEG is the main software which runs on a Windows-based computer/laptop where basic data is collected and controls the Q21. This software records the patient information and displays and stores the EEG. The Q21 system provides for typical EEG functions, including realtime EEG recording and viewing, adjustable vertical and horizontal display scale, adjustable highpass, lowpass, and notch filters, file import and export, offline review, the ability to show and hide individual channels, remontaging, and the ability to add event markers. The Q21 system supports both individual electrodes and standard 19-channel Electrocap electrode arrays. Each Q21 system consists of an amplifier, software, and components of a standard personal computer (monitor, keyboard, and mouse). The Q21 amplifier is a 19+1 channel, 24-bit, low-noise, non-multiplexed, battery-powered, optically-isolated amplifier. The "+1" channel can be used as an auxiliary physiological channel.

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Size used for the test set and the data provenance:

   • The provided document does not specify a test set sample size for "performance" testing in the traditional sense of a clinical or retrospective data study.
   • Instead, the "testing" for this device focuses on demonstrating substantial equivalence to a predicate device based on features and compliance with non-clinical performance standards. There is no indication of a dataset of patient EEG recordings being used as a test set for performance evaluation.
   • Data Provenance: Not applicable as no specific test set data (e.g., patient EEG recordings) was described for performance evaluation.

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

   • Not applicable. The document does not describe a study involving expert-established ground truth for a test set of EEG recordings. The evaluation is based on technical specifications and compliance with recognized standards compared to predicate devices.

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

   • Not applicable. There was no test set requiring ground truth adjudication by experts for performance evaluation.

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. The device is an Electroencephalograph (EEG) system for acquiring, recording, transmitting, and displaying physiological data, not an AI-assisted diagnostic tool for human readers.

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

   • Not applicable. The device itself is an EEG system; it is not an algorithm designed for standalone performance analysis described in the context of diagnostic interpretation. Its "performance" refers to its ability to accurately acquire and display EEG signals.

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

   • Not applicable. For this type of device (an EEG system), the "ground truth" for proving its functionality typically involves calibrated input signals and adherence to industry standards for electrical performance, rather than clinical ground truth like pathology or expert consensus on disease. The document states the device meets the requirements of specific external standards and underwent software verification and validation testing, which serve as the basis for demonstrating its functional performance.

8. The sample size for the training set:

   • Not applicable. The document does not describe a training set in the context of machine learning or AI. The EEG system itself is a data acquisition and display device, not an AI model that requires a training set.

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

   • Not applicable, as no training set was described.

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The SPARK Scan is intended to acquire, display, and store the electrical activity of a patient's brain obtained by placing two or more electrodes on the head to aid in diagnosis.

The SPARK Scan is intended for the acquisition, display, and storage of electroencephalogram (EEG) data. The SPARK Scan is intended to be used by EEG technicians, or appropriately trained Nurses and Medical Assistants practicing in any medical setting where EEG data collection may be required.

The SPARK Scan is an SaMD product that consists of the Edge Software and Data Storage and Communication Platform.

The Edge software runs locally on the user's device and consists of a User interface and the EEG hardware interface, including the electroconductive gel (K1117). The User Interface is a desktop application that (a) manages interaction with the EEG hardware interface, (b) facilitates set up and recording of EEG data, and (c) provides limited access to review of patient records according to the user's permissions.

The Data Storage and Communication Platform (Cloud Software): The Cloud software runs on a server managed by SPARK Neuro and contains no user interface. The Cloud Software is responsible only for managing (a) authorization and authentication of users and (b) storage, validation, and access to all data collected on the system.

The SPARK Scan is compatible with three 3rd-party accessory devices: an FDA-cleared EEG hardware system, a standard off-the-shelf-laptop, and FDA-cleared EEG Recording Viewing Platforms.

The provided text is a 510(k) summary for the SPARK Scan device. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving the device meets specific acceptance criteria based on performance metrics. The device is an electroencephalograph (EEG) intended to acquire, display, and store brain electrical activity to aid in diagnosis.

Here's an analysis of the provided information concerning acceptance criteria and study details:

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

The document does not explicitly state acceptance criteria in terms of performance metrics (e.g., accuracy, sensitivity, specificity) for the SPARK Scan's ability to "aid in diagnosis." Instead, the "Performance Testing Summary" section indicates:

• Non-Clinical Testing:
  • Software verification and validation testing
  • Cybersecurity Risk Analysis and Testing
  • Human Factors Use Related Risk Analysis
• Biocompatibility: Not applicable (no patient contact).
• Electrical Safety and Electromagnetic Compatibility: Not applicable (no hardware).
• Animal Testing: Not required.
• Clinical Testing: Not required.

The comparison table between the subject device (SPARK Scan) and the predicate device (Mitsar-EEG) highlights technological characteristics rather than performance metrics against acceptance criteria.

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

The document states, "Clinical testing is not required to support substantial equivalence." This implies there was no clinical test set of patient data used for performance claims. The "test set" for the reported performance appears to be related to software verification and validation, cybersecurity, and human factors, which are not described using patient data.

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)

Since no clinical testing on patient data with diagnostic outcomes was performed or required, there is no mention of experts establishing a ground truth for a test set in the context of diagnostic aid. The ground truth for software testing would be defined by specifications and requirements, not expert interpretation of medical data.

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

No adjudication method is described because no clinical test set requiring expert consensus for ground truth was used.

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 study was conducted or is mentioned. The device is described as software for acquiring, displaying, and storing EEG data, not as an AI-assisted diagnostic tool that aids human readers in interpretation. Clinical testing was deemed "not required to support substantial equivalence."

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

The SPARK Scan is described as an SaMD (Software as a Medical Device) product comprising Edge Software and a Data Storage and Communication Platform, compatible with third-party EEG hardware. Its function is to acquire, display, and store EEG data. It is not presented as an "algorithm only" device that provides a diagnostic output in a standalone capacity without human interpretation. It aids in diagnosis by providing raw EEG data, requiring "Medical Staff" (Intended User) for interpretation. Clinical testing was not required for its clearance.

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

For the non-clinical testing conducted (software V&V, cybersecurity, human factors), the ground truth would be defined by engineering specifications, security protocols, and human factors engineering principles, respectively. No medical ground truth (e.g., expert consensus on diagnosis, pathology, or outcomes data) was used or required for this submission.

8. The sample size for the training set

The document does not mention a training set for machine learning or AI algorithms, as the device's function is described as data acquisition, display, and storage, not as an AI diagnostic tool. Therefore, sample size for a training set is not applicable or provided.

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

Not applicable, as no training set for machine learning or AI is mentioned.

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The Cumulus Functional Neurophysiology Platform is intended for the acquisition, display and storage of electroencephalograph (EEG) obtained by placing electrodes on the head of adults and adolescent patients. The EEG signals are time-stamped.

The system can be used in the patient's home or a health care facility.

The Cumulus Functional Neurophysiology Platform is comprised of the Cumulus Headset which records EEG signals that are time-stamped.

The Cumulus software application runs on a mobile device running android software. The software has graphical user interface that provides guidance to the user to place the headset correctly. The EEG data is received from the headset via Bluetooth. The data received is synchronised and timestamped between the headset and app.

The Cumulus Medical Device Hub provides the user interface for health care professionals to view, download and review data from the recordings.

The Platform components are:
• Cumulus EEG Headset with embedded software, which includes:
• An adjustable shell into which 16 Ag/AgCl EEG conductive sensors are attached.
• A zippered pocket for holding the detachable electronics.
• Interface buttons, LEDs, micro USB socket.
• Plastic-encased 'Puck' electronics.
• Cumulus Mobile device with installed Cumulus Mobile App.
• Disposable mastoid sticky sensors
• Earphones
• Device stand
• Headset and mobile device chargers

Patient contacting materials are biocompatible, commercially sourced and are used in the headset without modifications.

The device and accessories are not sterile, nor intended to be sterilized.

The Cumulus Functional Neurophysiology Platform is intended for the acquisition, display, and storage of electroencephalograph (EEG) signals obtained by placing electrodes on the head of adults and adolescent patients. The EEG signals are time-stamped. The system can be used in the patient's home or a healthcare facility.

Here's a breakdown of the acceptance criteria and the study information:

1. Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list acceptance criteria in a quantitative format for the functional performance of the EEG acquisition. Instead, it demonstrates substantial equivalence to a predicate device (NeuralScan System, K192753) based on a comparison of technological characteristics. The "reported device performance" is derived from these comparisons.

Note: "SE" in the "Comparison Outcome" column refers to "Substantially Equivalent," meaning the differences do not raise new questions of safety or effectiveness when compared to the predicate device.

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

The document states that clinical testing was not required for this product category. Therefore, no "test set" in the context of a clinical performance study for diagnosing conditions using the EEG recordings is described or referenced. The assessment is based on non-clinical bench testing and comparison to an existing device.

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

As no clinical efficacy study or diagnostic accuracy study with a "test set" was conducted or required, there were no experts used to establish ground truth in this context.

4. Adjudication method for the test set

Not applicable, as no clinical test set for diagnostic performance was used.

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 performed or mentioned. This device is an EEG acquisition and display platform, not an AI-assisted diagnostic tool for interpretation.

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

No standalone algorithm performance study was reported. The device's primary function is data acquisition and display, which serves as input for human interpretation.

7. The type of ground truth used

Not applicable for clinical efficacy, as the submission focuses on hardware and software performance for signal acquisition and display (substantial equivalence). For the non-clinical bench testing (electrical safety, EMC, hardware/software verification, biocompatibility, human factors, etc.), the "ground truth" would be established by the specifications of the relevant international standards (e.g., IEC 60601 series, ISO 10993 series).

8. The sample size for the training set

Not applicable. This device is an EEG acquisition and display system; it does not involve AI/ML algorithms that require a "training set" for diagnostic performance.

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

Not applicable.

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The Okti System is intended for use in the recording, displaying, analysis, printing and storage of human biological parameters such as heart and muscle activity, eye movement, breathing and body movements to assist in the diagnosis of various neurological disorders. The Okti is designed for use in a hospital or other clinical environment. The Okti is only to be used under the direction of a physician.

The Okti is a physiological data acquisition device intended for conducting EEG studies. It is used in conjunction with a PC running Compumedics Profusion EEG software. Power is provided by either an internal Lithium-Ion battery or a POE 100BASE-TX network connection. Physically, the Okti comprises a base unit housing the battery and digital electronic circuits. A changeable module connects to the base unit and houses the analogue circuity and electrode connectors providing options for 32, 64 or 128 referential, or single ended, channels primarily intended for EEG. Each module includes several differential inputs for electrode-based signals such as ECG, EMG or EOG. All these inputs are class CF for patient safety. Patient physiological data is digitised using multiple 24-bit ADCs and filtered using fixed point FIR filters implemented internally to an FPGA located in the analogue module. The data is transferred to a generalpurpose processor in the base unit over a synchronous serial link. From there the patient data may be saved to a device internal SD card or sent to a remote PC over an Ethernet or Wi-Fi LAN connection. A Bluetooth interface is also included for connection to external devices such as an oximeter. The Okti system is available in Okti32, Okti64, or Okti128. These differ only in channel number.

The provided text describes a medical device, Okti, which is an Electroencephalograph (EEG) system. The document is a 510(k) premarket notification to the FDA, asserting the substantial equivalence of Okti to a previously cleared predicate device, the Grael EEG system.

While the document extensively covers the electrical, mechanical, and performance specifications of the Okti device and compares it to its predicate, it does not describe a study involving AI assistance, human readers, or the establishment of ground truth by multiple experts for diagnostic performance evaluation, as would be expected for a typical AI/ML-driven device. The device described here is an EEG recording device, not an AI or diagnostic algorithm. Therefore, many of the requested criteria related to AI/ML device performance evaluation (e.g., sample size for test/training sets, data provenance, number of experts, adjudication, MRMC study, standalone performance, type of ground truth for diagnostic accuracy) are not applicable or not provided in this specific document.

The "performance data" summary relates to the technical validation of the device's ability to accurately record and process physiological signals, ensuring electrical safety, electromagnetic compatibility, and adherence to established EEG standards. It's about the quality of the signal acquisition, not the diagnostic accuracy of an AI interpreting the signals or a human interpreting with AI assistance.

Based on the provided text, here's what can be extracted regarding acceptance criteria and device performance, focusing on the device's technical performance rather than diagnostic AI performance:

Acceptance Criteria and Reported Device Performance (Technical Validation)

The document focuses on demonstrating substantial equivalence to a predicate device (Grael EEG) by comparing technical, electrical, and physical specifications, and by conducting standard performance and safety tests for EEG acquisition devices.

Table of Acceptance Criteria and Reported Device Performance (Technical Parameters):

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Neuronaute with IceCap 2 & IceCap 2 Small is a system intended to acquire, display, store, archive, and periodically transmit EEG signals from the brain using a full montage array to enable review at a physician's office, hospital, or other remote locations. It allows remote access by users via the Neuronaute N-CLOUD which receives EEG signals from Neuronaute Head Module which sends transmissions to the cloud.

Neuronaute and its associated software are intended to assist in the diagnosis of neurological disorders. Neuronaute and its components do not provide any diagnostics conclusions or automated alerts of an adverse clinical event about a patient's clinical condition.

The device is for use by trained medical professionals for patients under medical supervision. The device is intended for use on adults and pediatrics. Neuronaute is not intended to replace direct communication with healthcare providers. The system data should not be used alone but should be used along with all other clinical data and exams to come to a diagnosis.

Neuronaute with IceCap 2 & IceCap 2 Small is a system intended to acquire, display, store, archive, and periodically transmit EEG signals from the brain using a full montage array. The system includes the Neuronaute Head Module, IceCap 2 & IceCap 2 Small electrodes, battery, Bioadapter with the IceAdapter, mobile app, and the Neuronaute N-CLOUD. The IceCap 2 and IceCap 2 Small are single-piece flexible printed circuit headsets with 21 EEG sensors (19 EEG channels, 1 reference and 1 ground), 4 skin adhesive areas and 2 connectors. The electrodes are made of Ag/AgCl sensors connected via conductive silver ink and insulated with dielectric ink. The system allows remote access by users via the Neuronaute N-CLOUD. An optional video system composed by N-way and N-Deo is available.

The provided text describes the Neuronaute with IceCap 2 & IceCap 2 Small system, an electroencephalograph device. However, it does not contain a detailed study proving the device meets specific acceptance criteria for diagnostic performance. Instead, the document focuses on demonstrating substantial equivalence to a predicate device (Neuronaute, K202334) through a comparison of technical characteristics and non-clinical testing.

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

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state quantitative acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, accuracy) or report such performance for the Neuronaute with IceCap 2 & IceCap 2 Small. The comparison table focuses on technical specifications and material changes relative to the predicate device.

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The iSyncWave is intended for prescription use in a health care facility to acquire, transmit, display and store primarily EEG and optional auxiliary signals for adults and children, not including newborns.

iSyncWave™ is a wireless EEG measurement device that applies dry EEG measurement technology to an international 10-20 system compliant size-adjustable headset. iSyncWave™ measures 19 channel EEG in real time and transfers the data through BLE wireless connection to the iSyncWave™ App. The data is displayed and recorded via the iSyncWave™ App. iSyncWave™ uses dry electrode technology, which doesn't require a preparation process(e.g., applyinq conductive gel), to obtain high quality EEG signals. Before measuring the EEG, you can check the impedance of each electrode under the impedance check screen in the iSyncWave™ app. An EEG amplifier, analog-to-digital converter and Bluetooth are built in the device. All EEG signal is sampled at 250 Hz and then converted to digital data at 24-bit resolution. This device measures overall EEG data using 19 EEG electrodes, 1 Reference cable and 1 ground electrode. The measured data can be digitally converted to common average, longitudinal and transverse montage. The measured data is automatically uploaded to a secure cloud server via Wi-Fi connection and saved securely. The data saved in the cloud server can be seen on the iSyncWave™ app.

The iSyncWave is an electroencephalograph (EEG) device intended for prescription use in healthcare facilities to acquire, transmit, display, and store EEG and optional auxiliary signals for adults and children (excluding newborns). The primary study proving the device meets its acceptance criteria is a non-clinical bench test comparison to a predicate device, the WR19 System by Zeto Inc. (K172735).

Here's the breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the iSyncWave are primarily demonstrated through a substantial equivalence comparison to its predicate device, the WR19 System (K172735), and compliance with various international standards for medical electrical equipment. The "reported device performance" entries below reflect how the iSyncWave either matches or is deemed equivalent to the predicate, or meets the technical requirements of the standards.

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

The provided document does not specify a separate "test set" in terms of patient data for evaluating diagnostic performance. The studies cited are primarily non-clinical bench tests focused on verifying compliance with various electrical, safety, software, and biocompatibility standards. The data provenance is related to these engineering and safety tests, not patient data from a specific country or whether it was retrospective/prospective.

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

This information is not provided in the document. The regulatory submission focuses on engineering and safety compliance, and substantial equivalence to a predicate device, rather than a clinical performance study requiring expert ground truth assessment for a diagnostic task.

4. Adjudication Method for the Test Set

This information is not applicable as there is no described clinical test set involving patient data and multiple expert readings for 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

There is no mention of a Multi Reader Multi Case (MRMC) comparative effectiveness study being performed or any assessment of human reader improvement with or without AI assistance. The device functions as an EEG acquisition and display system; the document does not describe AI-driven interpretation or assistance in EEG reading for diagnostic purposes.

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

There is no mention of a standalone algorithm performance study. The device is described as an EEG acquisition and display system, not one that performs automated diagnostic interpretation.

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

The ground truth used for the non-clinical bench tests would be the established technical specifications and performance limits defined by the international standards (e.g., IEC 60601-1 for basic safety, IEC 80601-2-26 for electroencephalographs performance), and the technical characteristics of the predicate device. This is not a clinical "ground truth" derived from patient outcomes or expert reads.

8. The Sample Size for the Training Set

This information is not provided as the submission describes a medical device for acquiring and displaying physiological signals (EEG), not a machine learning or AI algorithm that requires a training set of data.

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

This information is not applicable as there is no described training set for a machine learning or AI algorithm.

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The electroencephalographic system Seer Home is intended to acquire, display, and store the electro-physiological signals of the patient's brain obtained by placing electrodes on the patient scalp.

The Seer Home is intended to be used for such studies as electroencephalograph (EEG) and video EEG recording to aid in diagnosis of neurological disorders. The Seer Home does not draw any diagnostic conclusions.

Seer Home is not intended for use as life support equipment such as vital signs monitoring in intensive care units.

Seer Home is only to be used under the direction and supervision or EEG technologist or clinician.

The Seer Medical - Seer Home is an ambulatory electroencephalograph system designed to be used at the patient's home for up to week-long studies. The ambulatory EEG recorder (called "Seer Sense" or "Wearable") is worn around the patient shoulders. The Wearable has a single cable exiting from the bottom of the device and is routed inline to 3 disposable ECG electrodes which are positioned on the chest for ECG recording. Exiting from the rear of the Wearable is single flexible cable which has a junction at the top of the patient's head connected to the 22 EEG electrodes (disposable) which are positioned in the international '10-20' system for EEG recording.

The Wearable records the EEG and ECG signals and wirelessly transmits them to a nearby "Seer Sight Video Monitoring Hub" in the patient's house. The Video Monitoring Hub has two roles, first to store the wireless data from the wearable, and the second is to record video from an in-built camera that is synchronized to the EEG/ECG data. The use of the recorded video data provides additional information to the physician (such as body movement artifacts) to assist in diagnosis in the neurological conditions.

At the end of the study period (up to a week) the Wearable and Hub are returned back to the clinic for data download. The Seer Cloud Platform software downloads the data, stores the data, displays the EEG/ECG signals and video for reviewers to interpret, make annotations, and produce reports.

The Seer Home is intended to be used by qualified operators or physicians trained in the interpretation of EEG/ECG signals and visual cues of patient movements - and is viewed as a part of a range of assessments used by Neurologists to assist in making diagnosis of neurological conditions.

The accessories used with the Seer Home are disposable EEG electrodes, disposable ECG electrodes, Transport/Carry case, Medical Grade Power Adapter, IFU, and Rechargeable Batteries.

The Seer Home device, an electroencephalographic system, did not report any clinical study for assessing device performance against acceptance criteria. The submission states, "There is no clinical testing required to support the medical device as the indications for use are equivalent to the predicate device." It relies on technical evaluations and non-clinical performance data to demonstrate substantial equivalence to the predicate device, MobileMedTek ElectroTek (K170441).

The non-clinical performance data and findings are summarized as follows:

1. Acceptance Criteria and Reported Device Performance (Non-Clinical/Technical):

2. Sample size used for the test set and the data provenance:
No clinical test set was reported. The technical evaluations mentioned were performed on the device itself as part of verification and validation processes.

3. 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 was reported.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable as no clinical test set was reported.

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 study was reported. The device is for acquisition, display, and storage of EEG signals; it "does not draw any diagnostic conclusions" and as such, does not incorporate AI for diagnostic assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Not applicable. The device is a system for signal acquisition and display, not an AI algorithm performing diagnosis or analysis.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
Not applicable as no clinical test set with ground truth was reported. For technical evaluations, the ground truth was based on established industry standards and regulatory guidance for medical devices, such as IEC 60601-1, IEC 60601-1-2, IEC 60601-1-11, IEC 60601-2-25, IEC 60601-2-26, ISO 10993-1/5/10, ASTM D5276, and FDA/IEC guidance for software and usability.

8. The sample size for the training set:
Not applicable as no machine learning algorithm development with a training set was reported.

9. How the ground truth for the training set was established:
Not applicable as no training set was reported.

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WAV SCAN EEG System is intended for the acquisition, display, and storage of electrical activity of a patient's brain including electroencephalograph (EEG) and event-related potentials (ERP) obtained by placing two or more electrodes on the head to aid in diagnosis.

WAVi™ SCAN EEG system (WAVi™ SCAN 1.0) is intended for the acquisition, display, and storage of electrical activity of a patient's brain including electroencephalograph (EEG) and eventrelated potentials (ERP) obtained by placing two or more electrodes on the head to aid in diagnosis. The medical system includes the "WAVi™ EPU" (Electronic Processing Unit), an EEG amplifier intended to be used with EEG accessories cleared in K162460 and a computer (laptop computer or tablet device with internal battery and power cord). The hardware and ancillary components used in conjunction with WAVI™ SCAN 1.0 include an EEG cap, the WAVI™ EPU, headphones, a Subject Response Device and a Base Station laptop computer. The software on the Base Station laptop computer is intended for device programming. The WAVI EEG System's software includes electronic versions of standardized clinical assessment tools related to psychiatry and neuropsychological evaluation but are provided for convenience and are to be used in accordance with the assessment tools' specific general instructions. These tools do not interact with any other of the EEG system's hardware and software measures and are stand alone.

The WAVi Scan EEG System has acceptance criteria primarily related to its electrical performance and adherence to established medical device standards. The study presented is a pre-market notification (510(k)) submission to the FDA, which demonstrates substantial equivalence to predicate devices rather than a comparative effectiveness study in the traditional sense of human reader improvement.

Here's a breakdown of the acceptance criteria and the study's proof of meeting them:

1. Acceptance Criteria and Reported Device Performance

The acceptance criteria are derived from recognized international standards for electroencephalographs, particularly IEC 80601-2-26:2019, and general electrical safety and electromagnetic compatibility (EMC) standards. The study demonstrates conformance to these standards.

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