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The iSyncBrain-C is to be used by qualified medical or qualified clinical professionals for the statistical evaluation of the human electroencephalogram (EEG) in patients aged 4.5 to 81 years.

iSyncBrain-C is a software program for the post-hoc statistical analysis of the human electroencephalogram (EEG). EEG signals can be measured by various EEG equipment, and the measured EEG data is saved in EDF files. iSyncBrain-C can upload, and analyze these EDF files, and personal information or results are automatically stored in AWS (Amazon Web Serve). The analysis consists of the Fast-Fourier Transformation (FFT) of the data to extract the spectral power for each of the designated frequency bands (e.g., Delta, Theta, Alpha, Alpha2, Beta2, Beta3, Gamma) and frequency information from the EEG. These analysis results are displayed in statistical tables and topographical brain maps of absolute and relative power, power ratio, ICA components, power spectrum, occipital alpha peak, source ROI power(sLORETA) & connectivity(iCoh). All EEG devices has its own frequency characteristics which should be included for any data comparisons coming from different devices. iSyncBrain-C has an EEG amplifier matching module where frequency spectra are adjusted with calibration table between database amplifier and recording amplifier. In all over 33,000 measures are derived for comparison against carefully constructed and statistically controlled age-regressed, normative database in which the variables have been transformed and validated for their Gaussian distribution. Each variable extracted by the analysis is compared to the database using parametric statistical procedures that express the differences between the subject and an appropriate sex/aqematched reference group in the form of z-scores.

Here's an analysis of the provided text regarding the iSyncBrain-C device, focusing on acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document describes the iSyncBrain-C as a software program for post-hoc statistical analysis of human EEG. The performance data section primarily discusses software validation in accordance with FDA guidance, rather than specific diagnostic performance metrics like sensitivity or specificity. The substantial equivalence argument is based on functional and technical similarity to a predicate device (qEEG-Pro), not on meeting specific quantitative clinical performance thresholds.

Therefore, the "acceptance criteria" appear to be focused on software functionality and safety, and substantial equivalence to a predicate device in terms of features and intended use. Specific quantitative performance metrics for disease detection or classification are not explicitly stated as acceptance criteria in this document.

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

The document does not explicitly state a test set specifically for evaluating the performance of the iSyncBrain-C algorithm against a clinical ground truth. The "Performance Data" section primarily refers to "software validation" against Software Design Specifications.

However, the document mentions statistics regarding the normative database used by the device for comparison:

• Sample size for Normative Database (used for comparison during analysis):

  • Eyes closed: 1289 samples
  • Eyes Open: 1288 samples

• Data Provenance: Not explicitly stated (e.g., country of origin). The document mentions "carefully constructed and statistically controlled age-regressed, normative database," but details about its collection (retrospective/prospective) and origin are absent.

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

This information is not provided in the document. The document refers to software validation and substantial equivalence claims, not a clinical study where experts establish ground truth for a test set. The normative database used for comparison is mentioned, but how its "ground truth" (i.e., "normal" characteristics) was established, or by whom, is not detailed.

4. Adjudication Method for the Test Set

This information is not provided as there is no mention of a clinical test set requiring expert adjudication in the context of performance evaluation for the iSyncBrain-C algorithm itself.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not mentioned in the provided document. The device is described as a "software program for the post-hoc statistical analysis of the human electroencephalogram (EEG)" and its primary evaluation was software validation and substantial equivalence. There is no information about human readers' performance with and without AI assistance.

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

A standalone performance study of the algorithm's diagnostic accuracy (e.g., identifying specific EEG abnormalities or conditions) is not explicitly described in the provided text. The "Performance Data" section focuses on software validation against design specifications and claims of substantial equivalence based on functionality. While it performs analyses independently, the document does not present data from a study measuring its standalone clinical diagnostic performance against a ground truth.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

For the software validation, the ground truth appears to be the Software Design Specifications (SDS). The device was tested to ensure it met these specifications.

For the normative database against which individual patient EEGs are compared, the "ground truth" is implied to be a statistically controlled dataset representing "normal" age-regressed EEG patterns. However, the specific method used to establish this "normalcy" (e.g., expert review of all samples, lack of clinical symptoms/diagnoses) is not detailed. It's not a ground truth for a diagnostic task for the iSyncBrain-C itself, but rather a reference.

8. The Sample Size for the Training Set

The document does not explicitly mention a "training set" for the iSyncBrain-C algorithm. This suggests that if machine learning is involved in the analytical processes (beyond statistical comparisons to a normative database), the training data details are not provided. The reference to the "normative database" with 1289 (eyes closed) and 1288 (eyes open) samples is a reference database for comparison, not necessarily a training set for the algorithm's core functions.

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

Since a "training set" is not explicitly mentioned or detailed, the method for establishing its ground truth is not provided.

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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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