Abstract: Advanced computing methods have been studied and used in recent years to diagnose brain disorders like Schizophrenia. This is a severe mental disorder in which the secretion of specific ...
Abstract: Objective: This study focuses on enhancing the applicability of brain–computer interface (BCI) systems for spinal cord injury (SCI) patients through improvements in electroencephalography ...
Abstract: Motor imagery-based Brain-Computer Interfaces (BCIs) suffer from limited accuracy when the EEG dataset is recorded from naive BCI users due to noisy components. Neural networks capture more ...
Abstract: Emotional expression and interaction are fundamental aspects of daily life. Understanding emotions not only improves communication but also offers significant potential for medical ...
Abstract: This work introduces a robust hybrid CNN-LSTM framework designed for the reliable identification and categorization of epileptic seizures using electroencephalogram (EEG) signals. The model ...
Abstract: Hyperventilation (HV) alters cerebral blood flow and neural excitability, making it a crucial physiological stimulus for detecting neurocognitive dysfunctions like mild cognitive impairment ...
What should an elementary reading block look like? For such a common part of the school day, it’s surprising to find that there’s no one right answer. More than 40 states have passed legislation ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
Abstract: Epilepsy is a pathology of the central neural system that is characterised by an abnormality in electrical activity within the brain. This aberrant electrical activity causes a variety of ...
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