EEG Artifact Removal System for Depression Using a Hybrid Denoising Approach.

Introduction: Several computer-aided diagnosis systems for depression are suggested for use by clinicians to authorize the diagnosis. EEG may be used as an objective analysis tool for identifying depression in the initial stage to avoid it from reaching a severe and permanent state. However, artifact contamination reduces the accuracy in EEG signal processing systems.

Progress and Challenges in Physiological Artifacts' Detection in Electroencephalographic Readings.

Background: Electroencephalographic (EEG) recordings are used to trace neural activity within the cortex to study brain functioning over time.

Introduction: During data acquisition, the unequivocal way to reduce artifact is to avoid artifact stimulating events. Though there are certain artifacts that make this task challenging due to their association with the internal human mechanism, in the human-computer interface, these physiological artifacts are of great assistance and act as a command signal for controlling a device or an application (communication).

Advanced Spatially Specific Neurofeedback for Symptoms of Depression and Its Electroencephalographic Correlates.

Background: Biofeedback is a type of neurofeedback that delivers a graphical knowledge rich in multimedia for the brain waves and produces a feedback signal on brain activity using the multimedia skills of computers and, thus, teaches self-regulation. It has been examined as potential treatment in recent years.

Primary Study Objective: The aim of the present study was to recognize variations in symptoms of depression in terms of electroencephalogram (EEG) neuronal mechanisms underlying quantitative electroencephalography (QEEG) neurofeedback.

Electroencephalography-Based Source Localization for Depression Using Standardized Low Resolution Brain Electromagnetic Tomography - Variational Mode Decomposition Technique.

Background: Electroencephalography (EEG) may be used as an objective diagnosis tool for diagnosing various disorders. Recently, source localization from EEG is being used in the analysis of real-time brain monitoring applications. However, inverse problem reduces the accuracy in EEG signal processing systems.

EEG Derived Neuronal Dynamics during Meditation: Progress and Challenges.

Meditation advances positivity but how these behavioral and psychological changes are brought can be explained by understanding neurophysiological effects of meditation. In this paper, a broad spectrum of neural mechanics under a variety of meditation styles has been reviewed. The overall aim of this study is to review existing scientific studies and future challenges on meditation effects based on changing EEG brainwave patterns.