This paper presents an adaptive filtering method for removing ocular artifacts in the electroencephalogram (EEG) records. The major concern in analyzing EEG signals is the presents of ocular artifacts in EEG records caused due to various factors. It has become necessary to design specific filters to remove the artifacts in EEG records. In this method, we propose an adaptive filtering method, wh...

continuous four hours eeg (electroencephalogram) recordings and its power spectrum analysis using fast fourier transform (fft) in urethane anesthetized male charles foster rats were performed in two groups: open brain injury and p-cpa (para-chlorophenylalanine) pretreated before brain injury, respectively, and compared with the eeg power spectrum of control rats. the eeg power spectrum analysis...

the record of human brain neural activities, namely electroencephalogram (eeg), is generally known as a non-stationary and nonlinear signal. in many applications, it is useful to divide the eegs into segments within which the signals can be considered stationary. combination of empirical mode decomposition (emd) and hilbert transform, called hilbert-huang transform (hht), is a new and powerful ...

the recent literatures indicate that central nervous system (cns) is highly vulnerable to systemic hyperthermia induced by whole body heating on conscious animals. in the present study, cerebral electrical activity or eeg (electroencephalogram) following exposure to high environmental heat has been studied in moving rats. rats were divided into three group (i) acute heat stress-subjected to a s...

Acute hyperammonemic encephalopathy is generally associated with severe liver disease, manifesting neuropsychiatric symptoms including confusion, lethargy, seizure, coma, and even death. Electroencephalogram (EEG) a proven diagnostic, prognostic, therapeutic tool in patients acute chronic encephalopathies. EEG changes are background slowing theta to delta ranges, accompanied by presence of trip...

The representation of the human electroencephalogram (EEG) records by neurophysiologists demands standardized time-amplitude scales for their correct conventional interpretation. In a suite of graphical experiments involving scaling affine transformations we have been able to convert electroencephalogram samples corresponding to any particular sleep phase and relaxed wakefulness into each other...

the volterra model is widely used for nonlinearity identification in practical applications. in this paper, we employed volterra model to find the nonlinearity relation between electroencephalogram (eeg) signal and the noise that is a novel approach to estimate noise in eeg signal. we show that by employing this method. we can considerably improve the signal to noise ratio by the ratio of at le...

Electroencephalogram (EEG) is a neurotechnology used to measure brain activity via impulses. Throughout the years, EEG has contributed tremendously data-driven research models (e.g., Generalised Linear Models, Bayesian Generative and Latent Space Models) in Neuroscience Technology Neuroinformatic. Due versatility, portability, cost feasibility, non-invasiveness. It various Neuroscientific data ...

objective electroencephalogram (eeg) is an easy and non invasive evaluation method for diagnosis and early prognosis in children. our aim was to assess the association between eeg and the patients' developmental quotient (dq) level in phenylketonuria. materials & methods in this study, 94 pku patients (45 boys, 49 girls; mean age: 8.5 6.2 years) who were diagnosed through newborn screening test...