Higher-Order Phase-Space Reconstruction for Detection of Epileptic Electroencephalogram

In this paper, the authors propose a new technique for classification of seizures, non-seizures, and seizure-free EEG signals based on non-linear trajectories signals. The are decomposed using EMD to obtain intrinsic mode functions (IMFs). phase space these IMFs is then reconstructed novel higher-order dimensions (3D, 4D, 5D, 6D, 7D, 8D, 9D, 10D). existing techniques seizure detection have deployed 2D & 3D phase–space reconstruction only. Euclidean distance all PSR used as feature classify performance proposed method analyzed Bonn University database in which 7D accuracy 99.9% has been achieved both Random Forest classifier J48 decision tree.