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Imagination

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Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.

International journal of neural systems
Effective common spatial pattern (CSP) feature extraction for motor imagery (MI) electroencephalogram (EEG) recordings usually depends on the filter band selection to a large extent. Subband optimization has been suggested to enhance classification a...

Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

Computational intelligence and neuroscience
Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve ...

Generalisation, decision making, and embodiment effects in mental rotation: A neurorobotic architecture tested with a humanoid robot.

Neural networks : the official journal of the International Neural Network Society
Mental rotation, a classic experimental paradigm of cognitive psychology, tests the capacity of humans to mentally rotate a seen object to decide if it matches a target object. In recent years, mental rotation has been investigated with brain imaging...

Classification of hemodynamic responses associated with force and speed imagery for a brain-computer interface.

Journal of medical systems
Functional near-infrared spectroscopy (fNIRS) is an emerging optical technique, which can assess brain activities associated with tasks. In this study, six participants were asked to perform three imageries of hand clenching associated with force and...

Development of electroencephalographic pattern classifiers for real and imaginary thumb and index finger movements of one hand.

Artificial intelligence in medicine
OBJECTIVE: This study aimed to find effective approaches to electroencephalographic (EEG) signal analysis and resolve problems of real and imaginary finger movement pattern recognition and categorization for one hand.

Bridging the gap between motor imagery and motor execution with a brain-robot interface.

NeuroImage
According to electrophysiological studies motor imagery and motor execution are associated with perturbations of brain oscillations over spatially similar cortical areas. By contrast, neuroimaging and lesion studies suggest that at least partially di...

Ten-dimensional anthropomorphic arm control in a human brain-machine interface: difficulties, solutions, and limitations.

Journal of neural engineering
OBJECTIVE: In a previous study we demonstrated continuous translation, orientation and one-dimensional grasping control of a prosthetic limb (seven degrees of freedom) by a human subject with tetraplegia using a brain-machine interface (BMI). The cur...

Time-frequency modulation of ERD and EEG coherence in robot-assisted hand performance.

Brain topography
A better understanding of cortical modifications related to movement preparation and execution after robot-assisted training could aid in refining rehabilitation therapy protocols for stroke patients. Electroencephalography (EEG) modifications of cor...

What could be? Depends on who you ask: Using latent profile analysis and natural language processing to identify the different types and content of utopian visions.

The British journal of social psychology
When people think of a utopian future, what do they imagine? We examined (a) whether people's self-generated utopias differ by how much they criticize, seek to change or escape from an undesirable present; and (b) whether these distinct types of utop...

[Three-dimensional convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery electroencephalography signal].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The brain-computer interface (BCI) based on motor imagery electroencephalography (EEG) shows great potential in neurorehabilitation due to its non-invasive nature and ease of use. However, motor imagery EEG signals have low signal-to-noise ratios and...