Microprocessor-based EEG spike detection and quantification

A microprocessor-based system for the detection and quantification of sharp EEG waveforms is described. The hierarchical approach utilises initial transient detection based on computation of a second-derivative measure of curvature, followed by pattern-recognition and artifact-rejection routines based on consideration of specific waveform parameters. Initials results demonstrate an ability to approximate human-analysis results, while providing precise measures of amplitude, duration, and sharpness. The decreasing cost of microprocessors makes multichannel configurations economically feasible.