Abstract: A system and method for modeling bio-signals in the form of non-linear stochastic oscillators by extracting time series data from a subject into a series of summary fit parameters and comparing the unknown fit parameters to a set of normative fit parameters to determine whether the subject should be included in a group or not. The method includes data collection, feature extraction and then comparison of fit parameters from a non-linear stochastic oscillator model to a normative standard to make the in or out determination for a particular group. The system includes a processor programmed to perform the steps of the method.

Abstract: A system and method for modeling bio-signals in the form of non-linear stochastic oscillators by extracting time series data from a subject into a series of summary fit parameters and comparing the unknown fit parameters to a set of normative fit parameters to determine whether the subject should be included in a group or not. The method includes data collection, feature extraction and then comparison of fit parameters from a non-linear stochastic oscillator model to a normative standard to make the in or out determination for a particular group. The system includes a processor programmed to perform the steps of the method.

Abstract: A method of extracting brain frequency sub bands corresponding to a medical condition such as Alzheimer's Disease from EEG time series data of a patient includes the steps of applying wavelet transforms to the EEG time series data to generate a continuous wavelet transformation time series at each wavelet scale, calculating Wavelet Entropy (WE) and Sample Entropy (SE) directly from the Continuous Wavelet Transformation time series at each wavelet scale, calculating arithmetic or geometric means and accumulations across scale ranges of interest; and selecting data from major brain frequency sub-bands as candidate sets of extraction features for analysis as a diagnostic signature for the medical condition. Diagnostic signatures for Alzheimer's disease are found when values of WE or SE are in certain ranges when EEG data is collected and analyzed in connection with certain analytical tasks such as an Eyes Open task.