Sleep apnea is a growing sleep disorder issue and estimate to affect 7% of the adult population in Malaysia. In this study, the electrical activity of the brain is studied using Electroencephalogram (EEG). The data obtained was then decomposed using three methods; Empirical Mode Decomposition (EMD), Bivariate EMD and finally Ensemble EMD. The Index of Orthogonatility (IO) was obtained which sho...

The Electroencephalogram (EEG) is a biological signal that represents the electrical activity of the brain and is the main resource of information for studying neurological disorders. Corruption of EEG signal is caused by occurrence of various artifacts like line interference, electroculogram, electrocardiogram and muscle activity [3]. These artifacts resources increase the difficulty in analyz...

Background: Ensuring adequate depth of anesthesia during surgery is essential for anesthesiologists to prevent the occurrence of unwanted alertness during surgery or failure to return to consciousness. Since the purpose of using anesthetics is to affect the central nervous system, brain signal processing such as electroencephalography (EEG) can be used to predict different levels of anesthesia....

Introduction: In this paper, a novel complexity measure is proposed to detect dynamical changes in nonlinear systems using ordinal pattern analysis of time series data taken from the system. Epilepsy is considered as a dynamical change in nonlinear and complex brain system. The ability of the proposed measure for characterizing the normal and epileptic EEG signals when the signal is short or is...

We propose in this paper a feature extraction method to extract brain wave features from electroencephalography (EEG) signal. The proposed feature extraction method is based on an assumption that EEG signal could be considered as stationary if the time window is sufficiently short. With this assumption, EEG signal has some similar properties to speech signal and hence a feature extraction metho...

Biomedical signal monitoring and recording are an integral part of medical diagnosis treatment control mechanisms. For this, enhanced signals with appropriate peak preservation required. The OWA (OrderedWeighted Aggregation) Filter used in this paper helps non-linear filtering peaks for accurate diagnosis. Weights important aspect the filter, Gaussian method KDE (Kernel Density Estimation) func...

Electroencephalogram (EEG) is nothing but measuring electric activity of brain. EEG non-stationary signal. characterizes human behavior. There are many brain abnormalities that can be identified and treated using behavior analysis. As per researchers study Epilepsy commonly happening disorder getting spread over the time. It sudden stroke in where patient suffers from unusual activities seizure...

The article describes the classification of simple movements using a system based on Hidden Markov Models (HMM). Brisk extensions and flexions of the index finger, and movements of the proximal arm (shoulder) and distal arm (finger) were classified using scalp EEG signals. The aim of our study was to develop a system for the classification of movements which show EEG changes at identical scalp ...