The present invention provides a computer-implemented method, including: a. obtaining, in real-time, by a specifically programmed processor, electrical signal data representative of brain activity of a particular individual； b. processing, in real-time the electrical signal data representative of brain activity of a particular individual based upon a pre-determined predictor associated with a particular brain state, selected from a library of predictors containing a plurality of pre-determined predictors, wherein each individual pre-determined predictor is associated with a unique brain state, wherein the pre-determined predictor associated with a particular brain state includes: i. a pre-determined mother wavelet, ii. a pre-determined representative set of wavelet packet atoms, created from the pre-determined mother wavelet, iii. a pre-determined ordering of wavelet packet atoms, and iv. a pre-determined set of normalization factors, wherein the processing includes: i. causing, by the specifically programmed processor, the electrical signal data to be deconstructed into a plurality of pre-determined deconstructed wavelet packet atoms, utilizing the pre-determined representative set of wavelet packet atoms, wherein time windows of the electrical signal data are projected onto the pre-determined representative set of wavelet packet atoms wherein the projection is via convolution or inner product, and wherein each pre-determined representative wavelet packet atom corresponds to a particular pre-determined brain activity feature from a library of a plurality of pre-determined brain activity features； ii. storing the plurality of pre-determined deconstructed wavelet packet atoms in at least one computer data object； iii. causing, by the specifically programmed processor, the stored plurality of pre-determined deconstructed wavelet packet atoms to be re-ordered within the computer data object, based on utilizing a pre-determined order； iv. obtaining a statistical measur
