Comprehensive eeg-based substance quantification
OwnerKrishna Gandhiinventor
Life of this patent
Estimating the term…
Abstract
This invention presents a system using an alternative method to quantifying levels of substances from the EEG data using a non-linear equation based on the same essential features of previous disclosures. The essential features consist of predetermined frequency bands, the amalgamated ratio and a regression formula: (Formula (I)) where Y is the EEG-based substance level quantification.
Claims10
A comprehensive EEG-based substance level quantification system, method, comprising:
- a. Method Aspect:
- i. obtain EEG signal data
- ii. analyzing EEG data to obtain the average power(s) for each of its said predetermined frequency band(s);
- iii. calculating a value from the amalgamated ratio determined for said substance;
- and
- iv. obtaining a quantified level of said substance from S-curve equation:
- Y
- =
- L
- 1
- +
- e
- -
- k
-
- (
- x
- -
- x
-
- 0
- )
- v. Optionally, adapting the method to alternative quantification methods,
- wherein Y is said one substance level selected from hormones, neurotransmitters, neuromodulators, analyte and/or biomarkers.
- b. System Aspect:
- i. An EEG data acquisition module configured to receive or obtain EEG data;
- ii. analyse said EEG data and obtain the average power(s) for the predetermined frequency band(s);
- iii. calculate a value from the amalgamated ratio determined for said substance
- iv. and obtain a quantified level of said substance from equation of
- Y
- =
- L
- 1
- +
- e
- -
- k
-
- (
- x
- -
- x
-
- 0
- )
- wherein Y is said one substance level selected from hormones, neurotransmitters, neuromodulators, analyte and/or biomarkers,
- wherein Y is said one substance level selected from hormones, neurotransmitters, neuromodulators, analyte and/or biomarkers and wherein the claim encompasses both existing and earlier quantification approaches, regardless of the specific implementation
In a method or system according to any one of the preceding claims, wherein essential features of said methods are derived by AI-integrated configuration or machine learning processes from leading research insights embodied in previous linked patents and optimized to provide enhanced accuracy outcomes that quantify levels of substances from the EEG data and wherein said method is fully automated.
Dependencies are inferred from the claim text.