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  • M2500


  • The complexity of assessing all possible combinations of qEEG & ERP biomarker features scales up with the addition of each potential feature. Neuronetrix has implemented a flexible architecture to facilitate automated classification of aEEG/ERP data using artificial neural networks. The COGNISION™ Classifier module enables rapid testing and validation of meaningful combinations of qEEG/ERP biomarkers.
  • Features include:
    • Database: Entire classification system is built on the COGNISION™ Patient Manager database so all clinical biomarker information can be used in the classification model 
    • Meta Modeling: Easy and intuitive definition of classification model architecture (Class-Set, Feature Set, Training Set, Experts, Validation, etc.)
    • Data Fusion: Can combine data from qEEG and ERP tests (spectral properties, amplitude vs time, areas under the curve, wavelets, etc.)
    • Feature Fusion: Automatically extracts and combines groups of features using optimized experts (Support Vector Machine, Multi-Layer Perceptron, Random Forrest, etc.)
    • Decision Fusion: Combines decisions from multiple experts for final classification (Weighted Majority Voting, Stacked Generalization, etc.)
    • Model Validation: Implements automatic k-fold validation