Analysis of epileptic EEG signals using higher order spectra

Abstract

The unpredictability of the occurrence of epileptic seizures contributes to the burden of the disease to a major degree. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into these phenomena, thereby revealing important clinical information. Thus, various methods have been proposed to predict the onset of seizures based on EEG recordings. A seemingly promising approach involves nonlinear features motivated by the higher order spectra (HOS). The goal in this paper is to find the different HOS features for normal, pre-ictal (background) and epileptic EEG signals. This may help in the detection of seizure onset as early as possible with maximal accuracy. In this work, 300 EEG data, each belonging to the three classes, are studied. Our results show that the HOS based measures show unique ranges for the different classes with high confidence level (p = 0.002).

Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals

“…The computation of the bispectrum depends on the product of the three Fourier coefficients, as shown in (17). The phase entropies S1 and S2 are similar to spectral entropies, but computed from the bispectrum, and can be given by [54]:…”

Effects of Speech Phonological Features during Passive Perception on Cortical Auditory Evoked Potential in Sensorineural Hearing Loss

“…Several non-linear methods presented by previous researchers including sample entropy (SampEnt), higher order spectra (HOS), fractal dimension (FD) and recurrent quantification analysis (RQA) provide a better and valuable mechanism for result interpretation (Acharya et al 2015(Acharya et al , 2011Chua et al 2011Chua et al , 2009. For the last two decades, more exploration was conducted using nonlinear dynamic method in giving potential understanding as this technique extracts hidden complexity in the time series brain signal (Lehnertz 2008;Mormann et al 2005Mormann et al , 2003.…”

“…According to Acharya et al (2013), higher order spectra (HOS) method is considered as one of powerful mechanisms to justify the presence of abnormalities, besides usefulness in the event of signal distortion due to Gaussian noise. This framework has been persistently used in the field to study epilepsy disorder (Chua et al 2011(Chua et al , 2009.…”

Automated Glaucoma Detection Using Hybrid Feature Extraction in Retinal Fundus Images

“…Recent studies show that HOS can be used to diagnose epilepsy using Electroencephalogrphy (EEG) signals and cardiac abnormalities using heart rate signals 27,28 . HOS invariants have been used for shape recognition 29 and to identify different kinds of eye diseases 20,4 .…”