Spike detection using a syntactic pattern recognition approach
Syntactic methods were used to detect spikes utilizing time-domain features (slope and duration). The difference between this and earlier work is that here rules to discriminate each subject's spikes are automatically inferred from a training set consisting of sample spike waveforms obtained using expert knowledge, whereas the previous work used expert human knowledge to determine a set of universal rules. Therefore, the intersubject spike variability is accommodated in the design, without jeopardizing objectivity. The structural combination of the features is used by the syntactic method, providing a strict, explicit set of rules by which the spikes are identified. As a result, a rule-based definition for each subject's spike is obtained.<<ETX>>