Nonlinear dynamics and chaos theory have been used in neurophysiology with the aim to
understand the complex brain activity from electroencephalographic (EEG) signals …

The EEG (Electroencephalogram) signal indicates the electrical activity of the brain. They
are highly random in nature and may contain useful information about the brain state …

Abstract Background The EEG (Electroencephalogram) is a representative signal containing
information about the condition of the brain. The shape of the wave may contain useful …

The Electroencephalogram (EEG) is a representative signal containing information about
the condition of the brain. The shape of the wave may contain useful information about the …

Background Analysis of heart rate variation (HRV) has become a popular noninvasive tool
for assessing the activities of the autonomic nervous system (ANS). HRV analysis is based …

Throughout the years, major advancements have been made in the field of EEG-based
emotion classification. Implementing deep architectures for supervised and unsupervised …

The detection of seizure in the newborn is a critical aspect of neurological research. Current
automatic detection techniques are difficult to assess due to the problems associated with …

This paper reports a study of EEG data of epileptic patients in terms of multifractal detrended
cross-correlation analysis (MF-DXA). The EEG clinical data were obtained from the EEG …

Background While decoding visual and auditory stimuli using recorded EEG signals has
enjoyed significant attention in the past decades, decoding olfactory sensory input from EEG …

This survey provides a comprehensive overview of the different methods for detecting the
nonlinearity of the EEG signal. Electroencephalography (EEG) is a widely used signal for …