Abstract: The method for simultaneously and concurrently identifying and quantifying a wide variety of types of facial electromyographic (EMG) and eye movement electrooculargraphic (EOG) activity, which naturally contaminate electroencephalographic (EEG) waveforms in order to significantly improve the accuracy of the calculation in real-time of the amplitude and/or coherence of any brainwave activity for any chosen frequency bandwidth for any number of electrode placements. This multi-level, widely or universally applicable, pre-defined pattern recognition artifact detection and correction system provides a method for enhancing EEG biofeedback training by detecting and eliminating any brief, contaminated epoch of EEG activity from being included in the calculation and analysis of the EEG signal.