Abstract
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.
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Acknowledgment
This work has been supported by Ibnu Sina Institute, MyBrain15 from Ministry of High Education Malaysia and University Teknologi Malaysia.
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Ashaari, A., Ahmad, T., Zenian, S., Shukor, N.A. (2016). Selection Probe of EEG Using Dynamic Graph of Autocatalytic Set (ACS). In: Berry, M., Hj. Mohamed, A., Yap, B. (eds) Soft Computing in Data Science. SCDS 2016. Communications in Computer and Information Science, vol 652. Springer, Singapore. https://doi.org/10.1007/978-981-10-2777-2_3
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DOI: https://doi.org/10.1007/978-981-10-2777-2_3
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