(177 days)
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.
| Acceptance Criteria (Implied from the document) | Reported Device Performance |
|---|---|
| Software functionality (e.g., data upload, analysis, storage, display) | "The software was tested according to Software Design Specifications (SDS) as intended. The testing results support that all the software specifications have met each module's acceptance criteria and interaction of processes. The iSyncBrain-C passed all testing..." |
| Safety of operation | "iSyncBrain-C passed all testing and supported the claims of substantial equivalence and safe operation." |
| Substantial Equivalence to Predicate Device (qEEG-Pro) | "The information provided in this submission supports that iSyncBrain-C is the substantial equivalence to qEEG-Pro(K171414) and that the system is safe and effective for the users/operators." |
| Age Range for Statistical Evaluation | Statistical evaluation for patients aged 4.5 to 81 years. The normative database covers 4 to 82 years, aligning with the indication. |
| Frequency Bands for Analysis | 8 specified frequency bands (Delta, Theta, Alpha1, Alpha2, Beta1, Beta2, Beta3, Gamma). |
| Indicators Provided | Absolute power, Relative power, Power ratio, ICA component, Power spectrum, Occipital alpha peak, Source ROI power (sLORETA) & Connectivity (iCoh). |
| Compatibility with EEG equipment | Can upload and analyze EEG data in EDF files. Includes an EEG amplifier matching module to adjust frequency spectra. |
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:
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Sample size for Normative Database (used for comparison during analysis):
- Eyes closed: 1289 samples
- Eyes Open: 1288 samples
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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.
§ 882.1400 Electroencephalograph.
(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).