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39 articles for “brain activity”
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Neuroinformatics and Its Impact on the Future of Brain-Computer Interface Technology
Abstract: Neuroinformatics, a multidisciplinary field combining neuroscience, information technology, and data science, plays a crucial role in advancing brain-computer interface (BCI) technology. By leveraging large-scale neural data, machine learning algorithms, and computational models, neuroinformatics enhances our understanding of brain function and improves the design and development of BCIs. The integration of neuroinformatics into BCI systems offers new possibilities for interpreting complex brain signals, facilitating real-time communication between the brain and external …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 9–18 Read article
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Neurophysiological Effects of Chanting the Gayatri Mantra on Students of Allied Health Sciences: A Study among 1200 Students at Paramedical College, Desh Bhagat University
Abstract: Background: The Gayatri Mantra, a sacred Vedic chant, is traditionally believed to offer numerous benefits, including mental clarity, stress reduction, and cognitive enhancement. Despite anecdotal evidence supporting these claims, scientific research on its neurophysiological effects, especially within educational settings, remains limited. This study investigates the impact of chanting the Gayatri Mantra on brain activity, stress levels, and cognitive performance among 1200 students in the Allied Health Sciences program at Paramedical …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Brain Machine Interface: A Review of Current Technologies and Future Directions
Abstract: Brain Machine Interface (BMI) is a rapidly growing field that aims to establish direct communication between the brain and an external device. This technology has the potential to restore lost motor and sensory functions in people with neurological disorders or injuries. A brain-computer interface (BCI) is a technology that converts signals from the brain into instructions for computers or other gadgets. This innovation allows individuals to engage with their surroundings …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 14–24 Read article
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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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Deciphering the Pathophysiology of Migraine: Understanding Trigeminovascular System Activity and the Importance of the Gut-Brain Axis
Abstract: Migraine, a prevalent and disabling neurological condition, manifests in distinct phases: premonitory, aura, headache, postdrome, and interictal. Being a primary contributor to adult disability, it presents a substantial economic challenge on a global scale. Even with extensive research spanning centuries, the complete grasp of its root causes continues to evade us. This intricate neurovascular disorder primarily involves local vasodilation of intracranial and extracerebral blood vessels, coupled with simultaneous stimulation of …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 50–61 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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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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Smart Patient Monitoring and Motion Tracking System
Abstract: The integration of smart technologies in healthcare has revolutionized patient monitoring and diagnostics. This paper presents a Smart Patient Monitoring and Motion Tracking System designed for hospitals, leveraging EEG (Electroencephalogram) signals to track patient movements and monitor neurological health. The proposed system combines motion tracking with real time EEG signal analysis to enhance patient safety, especially for individuals prone to seizures, neurological disorders, or other mobility-related risks. The system employs …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 9–23 Read article
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An Intelligent Modelling system for Automotive Vehicles
Abstract: In this paper it’s about the development of artificial intelligence that has fuelled technological advancements. Self-driving automobiles are an example of an innovative development. Nowadays, you may work or sleep in your car while driving to your destination without touching the steering wheel or accelerator. This project aims to create a workable model of a self-driving car capable of traveling on multiple tracks, including curved, straight, and straight followed by …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 32–40 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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The Ethics and Implications of Brain–Computer Interfaces: Enhancing Human Abilities and Redefining Privacy
Abstract: This study addresses the ethical considerations and social implications of brain–computer interface (BCI) development and integration. BCI, sometimes called a brain-machine interface (BMI) or smart brain, is a direct communication path between the brain and electrical activity and an external device, usually a computer or robotic limb. BCIs are often directed towards researching, mapping, assisting, improving, or correcting human cognitive or sensorimotor functions. The implementation of BCIs varies from non-invasive …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 24–28 Read article
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Brain Tumor Detection Through CNN: Techniques, Dataset Insights, and Methodology
Abstract: Computer technologies are playing huge roles in some areas of the medical domain like surgery and therapy of different diseases. Researchers are doing studies and trying to experiment to detect different diseases like cancer, virus infections, and leprosy. There are many different medical imaging datasets that are publicly available for medical research purposes of diseases like cancer, virus infections, and leprosy, etc. where we can be able to access large …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 30–40 Read article
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Scientific Appraisal of Unani Drugs Used in Neurological Disorders
Abstract: Background: Neurological disorders are prevalent and are increasing. The Unani system of medicine provides insights into the pathogenesis, prevention, and treatment of these diseases. Objective: This study explores the Unani perspective on neurological disorders, focusing on therapies and the pharmacodynamics of related medicines. Methods: A comprehensive review of Unani literature was conducted using digital and traditional sources. Unani texts, like “Al Qanoon Fil Tib” by Ibn Sina and “Al Jami …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 1, 2026 · pp. 34–44 Read article
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Enhancing Control with Embedded Ssvep-Bci
Abstract: Brain–Computer Interface (BCI) technology establishes a direct communication link between the human brain and external devices without relying on muscular activity. Among various BCI paradigms, the Steady-State Visually Evoked Potential (SSVEP)-based approach has gained significant attention due to its high signal-to-noise ratio, minimal user training, and suitability for real-time applications. However, implementing such systems on embedded hardware presents challenges such as limited computational resources, signal noise, and latency in processing. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 41–52 Read article
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pH-Triggered In-Situ Nasal Gel Systems for Migraine Therapy: A Review
Abstract: Intranasal drug delivery has gained considerable attention as a non-invasive route for delivering drugs to both systemic circulation and the central nervous system, particularly for the treatment of migraine. Traditional nasal formulations such as sprays and drops often show poor therapeutic performance due to rapid mucociliary clearance and limited retention within the nasal cavity. To overcome these challenges, in-situ gel systems have been designed, which transform from a liquid to …
Published in Trends in Drug Delivery · Vol. 13, Issue 2, 2026 Read article
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Molecular Docking studies of Benzodiazepine Derivatives With GABA(B) Receptor
Abstract: Benzodiazepines (BZDs) are pharmacologically significant compounds that act by binding to GABA A neurotransmitter receptors, subsequently augmenting GABA-induced chloride ion flux, consequently inducing neuronal hyperpolarization. Benzodiazepines are commonly used in the treatment of sleep disorders, anxiety, muscle spasms, seizure disorders, and some forms of depression. The primary inhibitory neurotransmitter, GABA, functions on two types of receptors: the ligand-gated GABA A/C receptors and the G protein-coupled GABA B receptors. These neurotransmitters …
Published in International Journal of Toxins and Toxics · Vol. 1, Issue 2, 2024 · pp. 1–14 Read article
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Neuromorphic Spiking Neural Networks and Event-Driven Hardware: Architectures, Learning Paradigms, and Experimental Realizations
Abstract: With the current computational boom the research community is seeking for more sustainable energy efficient i.e. biologically inspired models of conventional Artificial Neural Networks (ANNs). Spiking Neural Networks (SNNs) known as the third generation of neural network models, provide a revolutionary approach by mimicking the asynchronized event-driven and temporally accurate signaling of the mammalian brain. Whereas conventional deep learning models operate with real-valued activations and dense matrix multiplications, SNNs use …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Significance of Physical Activities for Mental and Physical Health
Abstract: Physical activity is essential for maintaining both mental and physical health, providing wide-ranging benefits that enhance quality of life at all ages. Regular exercise, such as walking, cycling, swimming, or yoga, strengthens the cardiovascular system, boosts muscle and bone health, and improves metabolic function, which in turn reduces the risk of chronic conditions like diabetes, hypertension, and obesity. Beyond these visible benefits, consistent physical activity enhances flexibility, balance, and endurance, …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 1–6 Read article
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Advancements in Nanotechnology and Biosensor Integration for Detection and Treatment of Alice in Wonderland Syndrome
Abstract: Alice in Wonderland Syndrome (AIWS) is an uncommon neurological condition characterized by profound distortions in perception. Individuals with AIWS experience altered body image and spatial awareness, often perceiving objects, surroundings, or even their own body as being unusually large, small, or distorted. The condition presents a unique challenge for both diagnosis and management due to its elusive and varied symptoms. This paper explores how advancements in nanotechnology and biosensor integration …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 3, 2024 · pp. 1–12 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 Read article