SYSTEMS AND METHODS FOR THE PHYSIOLOGICAL ASSESSMENT OF BRAIN HEALTH AND THE REMOTE QUALITY CONTROL OF EEG SYSTEMS

• US 20150038869A1
• Filed: 07/13/2012
• Published: 02/05/2015
• Est. Priority Date: 07/16/2011
• Status: Abandoned Application

• Current Assignee: Cerora, Inc.
• Original Assignee: Cerora, Inc.
• Inventors: Devilbiss, David M., Simon, Adam J.
• Application Number:
  US14/233,292
• Publication Number:
  US 20150038869A1
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: A61B 5/377 using evoked responses
• CPC Class Codes: A61B 5/4088 Diagnosing of monitoring cognitive diseases, e.g. Alzheimer, prion diseases or dementia
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: G01D 18/002 Automatic recalibration G01D18/008 takes precedence

Abstract

A system for calibrating and/or verifying system performance of a remote portable EEG system having at least one EEG sensor. Embodiments of the invention can provide various reference signals to calibrate and quality control the remote performance of the data acquisition EEG system. In addition a calibration cable connects a reference signal source to the EEG sensors to enable remote calibration and quality control assessment. Further, a diagnostic biomarker is included to assess the state or function of a subject'"'"'s brain and enables the classification, prognosis, diagnosis, monitoring of treatment, or response to therapy applied to the brain by measuring any one of a list of candidate features extracted from a given cognitive or sensory task, and measuring changes in the EEG feature and task combination over time, among multiple states, or compared to a normative database.

Claims

1. A system for calibrating and/or verifying system performance of a remote portable EEG system having at least one EEG sensor, comprising:

at least one ground electrode;

a signal generator producing at least one channel of reference signals;

a wired cable assembly that connects the signal generator output to at least one EEG sensor and ground electrode; and

a programmed processor that generates test reference signals and collects responses generated by the EEG sensor to the test reference signals to confirm system calibration and and/or verify system performance of the remote portable EEG system.

2. The system of claim 1 wherein the signal generator includes a sound card assembled into a microprocessor based device.

3. The system of claim 1 wherein the reference signals generated include linear combinations of sine, square, and triangle waves of varying frequency and amplitude.

4. The system of claim 1 wherein the reference signals generated include a short circuit between the reference signal and ground enabling a short circuit noise assessment.

5. The system of claim 1 wherein the programmed processor is programmed with software algorithms that enable the coordination of the generation of reference signals and the data collection of such reference signals for automated system verification and validation.

6. The system of claim 1 wherein the wired cable assembly contains a voltage divider to diminish test reference signal amplitudes to physiologically relevant levels.

7. The system of claim 1 wherein the wired cable assembly contains a removable voltage divider to diminish test reference signal amplitudes to physiological levels when in place or to calibrate reference signal amplitudes on an individual device by device level when removed from the wired cable assembly.

8. A system for assessing the state or function of a subject'"'"'s brain, comprising:

a portable EEG sensing device that acquires a subject'"'"'s EEG signal data during cognitive or sensory testing; and

a feature extraction system that processes the subject'"'"'s EEG signal data to establish a noninvasive biomarker in the brain that enables the classification, prognosis, diagnosis, monitoring of treatment, or response to therapy applied to the brain by measuring an extracted EEG feature or EEG features from a measured EEG signal when conducting a predetermined cognitive or sensory task, feature extraction system further measuring changes in the extracted EEG feature or EEG features over time, among multiple states, or compared to a normative database.

9. The system of claim 8 wherein the feature extraction system establishes a biomarker by assessing each block of EEG signal data from the subject to create a list of features, variables or metrics extracted from each block of EEG signal data collected during an individual cognitive task, said list of features, variables or metrics including at least one of:

relative and absolute delta, theta, alpha, beta and gamma sub-bands, the theta/beta ratio, the delta/alpha ratio, the (theta+delta)/(alpha+beta) ratio, the relative power in a sliding two Hz window starting at 4 Hz and going to 60 Hz, the 1-2.5 Hz power, the 2.5-4 Hz power, the peak or mode frequency in the power spectral density distribution, the median frequency in the power spectral density, the mean or average (1^st moment) frequency of the power spectral density, the standard deviation of the mean frequency (square root of the variance or 2^nd moment of the distribution), the skewness or 3^rd moment of the power spectral density, and the kurtosis or 4^th moment of the power spectral density.

10. The system of claim 8 wherein the EEG feature or EEG features extracted by the feature extraction system includes the relative power spectral density within the 18<

=f<

=20 Hz frequency range of a measured EEG signal when conducting the predetermined cognitive or sensory task, said feature extraction system further establishing a cut-point between 0 and 100 percent for the relative power spectral density across the 18-20 Hz range.

11. The system of claim 8, wherein the non-invasive biomarker comprises statistically significant EEG features of Alzheimer'"'"'s Disease based on the p-value of a statistical significance test applied to the subject.

12. The system of claim 8 wherein the predetermined cognitive or sensory task is a resting state Eyes Open task or Eyes Closed task.

13. The system of claim 8 wherein the predetermined cognitive or sensory task includes at least one of a Fixation task, a CogState Attention task, a CogState Identification task, a CogState One Card Learning task, a CogState One Card Back task, a Paced Arithmetic Serial Auditory Task (PASAT), a King-Devick Opthalmologic task, a neuro-opthalmologic task, a monaural beat auditory stimulation task, a binaural beat auditory stimulation task, an isochronic tone auditory stimulation task, a photic stimulation task, an ImPACT task, a SCAT2 task, a BESS task, a vestibular eye tracking task, or a dynamic motor tracking task.

14. The system of claim 8, wherein the feature extraction system further diagnoses a disease state of a brain and nervous system of a subject by acquiring EEG signal data of the subject during a resting state task using said portable EEG sensing device, measuring the relative power spectral density of the subject'"'"'s EEG signal data in a designated frequency sub-band, applying a predetermined cut-point to dichotomize the power spectral density results into one or more biomarker states or classes, and determining which biomarker class a subject belongs to based on the subject'"'"'s individual power spectral density measurement relative to the predetermined cut-point.

15. The system of claim 8, wherein the feature extraction system extracts an EEG feature or EEG features by applying discrete or continuous wavelet transformation analysis to the subject'"'"'s EEG signal data to identify statistically meaningful features.