Abstract
Since the power spectral analysis of a non-Gaussian process generated by a nonlinear mechanism e.g., EEG, does not provide much information on the underlying nonlinear dynamics due to the lack of phase information, the higher-order statistics such as the bispectra are used to better understand the underlying nonlinear dynamics e.g., the quadratic phase coupling phenomena. The quadratic phase couplings have been observed in the EEG by the researchers over a decade for many diagnostic applications such as epilepsy, sleep, mental states. This study discusses the use of bispectral analysis of the EEG recorded from the posterior region of the head of the brain tumor patient in quantifying the quadratic phase couplings to indicate the presence of the tumor. The Bicoherence Index (BCI) or simply the Bicoherence (BIC) has been used for the purpose. Self-couplings (around 27-52%) in the [8-13] Hz (alpha) band and phase couplings (around 23-42%) in the [1-8] Hz (delta-theta) band have been observed for the normal subjects while only self-couplings (around <6.5% and around 40-53%) have been seen in both bands for the brain tumor patients. Significant lowering of coupling strengths (from 38.15% (±12.76%) to 3.51% (±3.28%)) in the alpha band and mild increase of them (from 32.76% (±18.73%) to 45.49% (±17.49%)) in the delta band have been observed for the brain tumor patients. The Power Ratio Index (PRI) based on the power spectrum is only statistically inferior (p>0.05) to the BIC in discriminating the brain tumor case from the normal one.
Highlights
Diagnosis and subsequent treatment are either missed or delayed in 69% of the brain tumor cases due to the fact that the most of the brain tumor symptoms are highly misleading and around 26% of these cases suffer a delay of more than a year before proper diagnosis (MFBTRI, 2013)
This study discusses the use of bispectral analysis of the EEG recorded from the posterior region of the head of the brain tumor patient in quantifying the quadratic phase couplings to indicate the presence of the tumor
The results of the test for determining the stationary segments using the second-order weak stationarity criterion are shown in Fig. 1a and b from two exemplary EEG records, one being the brain tumor and the other, normal
Summary
Diagnosis and subsequent (early) treatment are either missed or delayed in 69% of the brain tumor cases due to the fact that the most of the brain tumor symptoms are highly misleading and around 26% of these cases suffer a delay of more than a year before proper diagnosis (MFBTRI, 2013). Once the brain tumor symptoms are found, the advanced neuroimaging techniques such as MRI and CT or biopsy are not immediately suggested due to the following facts: They are either costly or invasive or do involve risks like hazardous radiation, especially in case of children, pregnant women and patients with implant devices (Black, 2010). Since an early treatment increases the survival rate, a better method that does not involve much cost, risks or complexity is required to reduce the delay in the diagnosis of the brain tumors (Black, 2010). One such option is the use of the scalp Electroencephalograms (EEGs) (Fattal-Valevski et al, 2012).
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