Selection probe of EEG using dynamic graph of autocatalytic set (ACS)

Electroencephalography (EEG) machine is a medical equipment which is used to diagnose seizure. EEG signal records data in the form of graph which consist of abnormal patterns such as spikes, sharp waves and also spikes and wave complexes. This pattern also come in multiple line series which then give some difficulties to analyze. This paper introduce the implementation of dynamic graph of Autocatalytic Set (ACS) for EEG signal during seizure. The result is then compared with other publish method namely Principal Component Analysis (PCA) of same EEG data