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14 articles for “electroencephalography”
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Steady State Visual Evoked Potential Based Brain Computer Interface System
Abstract: The steady-state visual evoked potential (SSVEP) is a brain response that can be measured by an electroencephalogram (EEG) when a subject looks at periodic luminance- or contrast-modulated stimuli. In this study, flickering Light Emitting Diode (LED) is used as visual stimulation. Mostly, brain response is recorded using an electroencephalograph (EEG) and recorded in the brain's occipital lobe which is associated with human vision. The study encompasses key stages, beginning with …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 35–43 Read article
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Evaluation of OTA Amplifier Using EEG Signals
Abstract: AbstractOver the last few years, there has been a tremendous exploration in VLSI industries in response to scaling trends towards deep submicron technology. Demand for low power and efficient amplification are rising in day-to-day life. In the process of scaling the CMOS nanometer demand low supply, which is helped to design digital circuit realization at very low power consumption. But it is not valid for analog circuit realization. The related …
Published in Trends in Opto-electro & Optical Communication · Vol. 10, Issue 2, 2020 · pp. 5–14 Read article
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Neuromarketing a New Tool for Marketing Research
Abstract: In recent years, a new marketing research tool called neuromarketing has emerged that uses brain research in a management context and has become popular in curricula and the world of practice. Neural Production caught the attention of publishers in early 2002 by making the publisher's job easier by simplifying the way and process of searching for ideas. This article examines the role of neuromarketing theory as a useful tool for …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 2, 2023 · pp. 20–26 Read article
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 Read article
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Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis
Abstract: Electroencephalography (EEG) has been very important in the detection of epileptic seizures so as to enable successful diagnosis, surveillance and therapy of epilepsy. Nevertheless, EEG electrodes based on traditional metals may be limited due to high or high contact impedance, lack of biocompatibility, discomfort to patients and prone to motion artifacts, which interfere with signal quality and diagnostic adequacy. The recent progress in material science has resulted in coming up …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 Read article
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Paediatric Epilepsy: Current Advances in Diagnosis and Management
Abstract: Paediatric epilepsy is one of the most common chronic neurological disorders of childhood, characterised by recurrent unprovoked seizures resulting from abnormal neuronal activity. Accurate diagnosis is essential and is based on a detailed clinical history, seizure semiology, neurological examination, and electroencephalography (EEG), with neuroimaging such as magnetic resonance imaging (MRI) used to identify structural abnormalities. Classification according to seizure type and underlying aetiology genetic, structural, metabolic, immune, infectious, or unknown—guides …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 53–68 Read article
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Brain And Gesture Controlled Assistive System For Physically Challenged Individuals
Abstract: Assistive communication technologies are essential for improving the independence of individuals with physical and sensory disabilities. This paper presents the design and implementation of a multimodal assistive system that integrates brain signal acquisition and gesture recognition for real- time communication. The system utilizes an Electroencephalography (EEG) sensor to capture neural activity and a PAJ7620 gesture sensor along with an ADXL335 accelerometer to detect hand movements. The acquired signals are processed …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 1, 2026 · pp. 36–43 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 1–8 Read article
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A Review on Detection of Autism Spectrum Disorder Using Signal Processing
Abstract: AbstractAutism is a neural developmental disability associated with impairments in communication and social interaction; it can be detected by various methods such as Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG). MRI is a technique which captures the image of various sections of brain. It is categorised as structural MRI (sMRI) and functional MRI (fMRI). The detection involves capturing the image, removing the unwanted regions of brain, segmenting the images and …
Published in Current Trends in Signal Processing · Vol. 8, Issue 2, 2018 · pp. 12–24 Read article
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Entropy Analysis Based Differential Evolution Approach for Emotion Classification for EEG
Abstract: Electroencephalography (EEG) signal processing is having its significance in various applications related to the emotion recognition and classification. The behavior monitoring, behavior class identification, emotion class identification are the major aspects for classification of EEG signal. In this paper, a feature adaptive differential evolution (DE) approach is defined to perform emotion classification. In this work, we used discrete wavelet transform (DWT), for extracting the statistical features from the EEG signal …
Published in Current Trends in Signal Processing · Vol. 5, Issue 3, 2015 · pp. 15–22 Read article
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Music on Mind and Body: A Simultaneous EEG and EMG Study to Quantify Emotions from Hindustani Classical Music
Abstract: With the advent of various techniques to assess the bioelectric signals on the surface of the body, it has become possible to develop various human-computer interface systems. In this study, for the first-time a cross- correlation based data is reported for two-different types of bio-signals viz. EEG (Electroencephalography) and EMG (Electromyography). Whereas EEG refers to the neuro-electric impulses generated in the brain recorded in the form of electric potentials, EMG …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 2, 2019 · pp. 27–38 Read article