1. A method of detecting seizures in an electroencephalogram (EEG) signal comprising the steps of: i) generating an EEG signal from a set of electrodes applied to an animal's cranium and obtaining an inverted version of the EEG signal; ii) obtaining representative numerical data from the EEG signal, wherein the representative numerical data is obtained by comparing the EEG signal to an averaged EEG signal to locate intersection positions to determine the location of each peak or trough of the EEG signal and recording the position of each trough, subsequent peak and two corresponding intersection points in respective data groups, wherein obtaining representative numerical data is carried out on the inverted version of the EEG signal, and the representative numerical data from both the EEG signal and inverted version of the EEG signal are combined; iii) characterizing the waveform shape of the EEG signal at a plurality of times within the EEG signal; iv) carrying out at least one calculation on at least some of the representative numerical data to produce related numerical data indicative of at least two individual oscillations identified within the EEG signal; v) comparing the related numerical data indicative of at least two individual oscillations identified to a predetermined criteria; and vi) determining that a seizure event has taken place at a particular time or times in the EEG signal if the related numerical data indicative of at least two individual oscillations identified at said particular time or times in the EEG signal are within the predetermined criteria; wherein a computer is configured to perform the steps i)-vi) above.