Brain Signals
Moving one dimensional cursor using extracted parameter from brain signals
... This study focuses on developing a method to determine parameters to control cursor movement using noninvasive brain signals, or electroencephalogram (EEG) for brain-computer interface (BCI). Two ...
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Security Solutions Using Brain Signals
... A brain computer interface is a direct neural interface or a brain–machine ...human brain and the computer ...uses brain signals for the authentication of ...(EEG) signals are ...
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State-space modeling and estimation for multivariate brain signals
... of brain signals was further demonstared in recent studies on brain connectivity analysis which has discovered the functional connectivity patterns changing over time, especially for task-related ...
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Towards predicting a realisation of an information need based on brain signals
... toring brain activity can lead to accurate predictions of a realisation of IN ...their brain activity was being monitored using functional Magnetic Resonance Imaging (fMRI) ...collective brain ...
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Mental State Detection in Classroom Based on EEG Brain Signals
... human brain waves in different states non-invasively, and to distinguish them into different levels of mental states in order to provide immediate mental state feedback to a classroom instructor and maximize ...
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BRAIN SIGNALS EXTRACTION FOR THE CONTROL OF A PROSTHETIC HAND
... between brain and computer provides the possibility of transmitting information in form of electrical ...the brain using non-invasive electrodes (non Invasive BCI) or on the surface of the brain ...
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On Similarities and Differences of Invasive and Non Invasive Electrical Brain Signals in Brain Computer Interfacing
... electrical brain signals, we repeatedly perceived a controversy on the origin, or the underlying source of those ...BCI signals are different, they rely on the same underlying ...electrical ...
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Classification of SSVEP Based Brain Signals using Discrete Wavelet Transform
... A Brain Computer Interface (BCI) is an alternative communication pathway, bypassing the normal cortical-muscular ...human brain and external device. A BCI translates brain signals of a BCI ...
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Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals
... the brain-relevance paradigm requires the relevance of an individual word to be inferred from the individual’s brain ...the brain activity findings related to the semantic oddball (introduced in the ...
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Predicting term-relevance from brain signals (Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval)
... from Brain Signals (TRPB) is proposed to automatically detect relevance of text infor- mation directly from brain ...on brain signals alone. Relevance was also associated with ...
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Brain Signals and Alcoholism
... the brain. Abnormal electricity of the brain may represent many brain disorders, which can be detected by analyzing EEG signal ...these signals directly in the time domain just by observing ...
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Analysing EEG brain signals using independent component analysis techniques
... of signals depends on the number of vanishing moments of the wavelet function used thus wavelets with a high number of vanishing moments lead to a more compact signal representation and are hence useful in coding ...
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Selecting Statistical Characteristics of Brain Signals to Detect Epileptic Seizures using Discrete Wavelet Transform and Perceptron Neural Network
... EEG signals were limited by a low-pass filter and impulse ...EEG signals, sub-bands have more accurate information about neurons ...original signals due to specific ...Decomposing signals into ...
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Simulating brain signals : creating synthetic EEG data via neural-based generative models for improved SSVEP classification.
... In [9], the authors propose deep EEG super-resolution using a GAN. The model is applied to a small number of EEG channel data to interpolate other channel signals using motor imagery dataset from [28]. The ...
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Analysing EEG brain signals using independent component analysis techniques
... The use of electroencephalography (EEG) in the medical field is evident in the effect it has on diagnosis and treatment of patients who suffer from some form of brain problem. These signals however once ...
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Emotion walking for humanoid avatars using brain signals
... speak, brain interfaces and other ...combining brain signals, facial muscle tension recognition and glove tracking to change the facial expression of humanoid avatars according to the user’s ...
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Nonlinear complexity analysis of brain fMRI signals in schizophrenia
... that brain signals from schizophrenia constitute a complex dysregulation of neurobiological and behavioural patterns rather than a simple up and down regulation ...
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Decoding Motor Signals From the Pediatric Cortex: Implications for Brain-Computer Interfaces in Children
... ECoG brain signals in children to determine the decodability of the brain signals and the feasibility of BCI ...trical signals from children’s brains can be successfully decoded and ...
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Fusion of musical contents, brain activity and short term physiological signals for music-emotion recognition
... input brain signals, extract the correspondent features, and outputs a CSV file ready to be incorporated in machine learning ...input brain signals and extracts different features from ...
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Title: Classification of Motion and Speech Based Brain EEG Signals using Bilayer Bayesian Classifier with Association Rule (BBC-AR)
... developing Brain Computer Interface (BCI) system which uses EEG ...from brain activity of healthy ...pre-processed signals and classify them into their respective alpha, beta, delta and gamma signal ...
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