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.
D000703:Analog-Digital Conversion; D003201:Computers; D004311:Double-Blind Method; D004569:Electroencephalography; D005069:Evaluation Studies as Topic; D006801:Humans; D008838:Microcomputers; D010363:Pattern Recognition, Automated