Abstract: A data processing method for detecting and classifying a segment of a signal that is obtained from a single-channel EEG-recording as a target signal segment or as a non-target signal segment. The method includes a voting process to determine whether classification of a first detected segment of the signal as a target signal segment or classification of a second detected segment of the signal as a non-target signal segment is correct. A device and a system that are configured and arranged to perform the data processing method.

Abstract: Methods and apparatus for encephalography process encephalography data to yield components that correspond to modular areas of the brain. In some embodiments encephalography data is processed by independent component analysis to yield a first set of components that are processed to generate a spectral filter. The spectral filter is applied to the encephalography data to generate a second set of components. The second set of components may be represented by one or more matrices. In an embodiment the second set of components is represented by weight and sphereing matrices. Methods and apparatus may be applied for monitoring brain function, selecting participants for medical trials, adjusting drug dosages, performing and monitoring biofeedback methods, detecting progression toward diseases or conditions that affect the brain and other applications.