AIMC Topic: Imagination

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Influence of a robotic companion on women's food choices: Evidence from an imaginary task.

Applied psychology. Health and well-being Aug 23, 2024
Previous research has demonstrated the influence of commensal dining between humans on food choices, whereas we conducted two studies to examine how the presence of a robot might influence people's choices between meat-heavy and vegetable-forward mea...
Imagination Choice Behavior Robotics Vegetables Food Preferences Humans Adult Male Female Young Adult
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Independent Vector Analysis for Feature Extraction in Motor Imagery Classification.

Sensors (Basel, Switzerland) Aug 22, 2024
Independent vector analysis (IVA) can be viewed as an extension of independent component analysis (ICA) to multiple datasets. It exploits the statistical dependency between different datasets through mutual information. In the context of motor imager...
Electroencephalography Movement Humans Imagination Algorithms Signal Processing, Computer-Assisted Support Vector Machine Brain-Computer Interfaces
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Benchmarking brain-computer interface algorithms: Riemannian approaches vs convolutional neural networks.

Journal of neural engineering Aug 21, 2024
To date, a comprehensive comparison of Riemannian decoding methods with deep convolutional neural networks for EEG-based brain-computer interfaces remains absent from published work. We address this research gap by using MOABB, The Mother Of All BCI ...
Evoked Potentials, Visual Imagination Humans Neural Networks, Computer Electroencephalography Algorithms Benchmarking Brain-Computer Interfaces
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Wasserstein generative adversarial network with gradient penalty and convolutional neural network based motor imagery EEG classification.

Journal of neural engineering Aug 14, 2024
Due to the difficulty in acquiring motor imagery electroencephalography (MI-EEG) data and ensuring its quality, insufficient training data often leads to overfitting and inadequate generalization capabilities of deep learning-based classification net...
Neural Networks, Computer Deep Learning Electroencephalography Brain-Computer Interfaces Wavelet Analysis Imagination Humans
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DSFE: Decoding EEG-Based Finger Motor Imagery Using Feature-Dependent Frequency, Feature Fusion and Ensemble Learning.

IEEE journal of biomedical and health informatics Aug 6, 2024
Accurate decoding finger motor imagery is essential for fine motor control using EEG signals. However, decoding finger motor imagery is particularly challenging compared with ordinary motor imagery. This paper proposed a novel EEG decoding method of ...
Machine Learning Algorithms Female Humans Signal Processing, Computer-Assisted Fingers Imagination Brain-Computer Interfaces Adult Male Electroencephalography
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Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Aug 6, 2024
Robotic arms are increasingly being utilized in shared workspaces, which necessitates the accurate interpretation of human intentions for both efficiency and safety. Electroencephalogram (EEG) signals, commonly employed to measure brain activity, off...
Calibration Brain-Computer Interfaces Adult Imagination Robotics Female Humans Male Electroencephalography Reproducibility of Results Neural Networks, Computer Speech Arm Young Adult Algorithms
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Human-robot interaction in motor imagery: A system based on the STFCN for unilateral upper limb rehabilitation assistance.

Journal of neuroscience methods Aug 5, 2024
BACKGROUND: Rehabilitation training based on the brain-computer interface of motor imagery (MI-BCI) can help restore the connection between the brain and movement. However, the performance of most popular MI-BCI system is coarse-level, which means th...
Female Young Adult Adult Humans Neural Networks, Computer Algorithms Electroencephalography Brain-Computer Interfaces Upper Extremity Imagination Male Deep Learning Robotics
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EEG-VTTCNet: A loss joint training model based on the vision transformer and the temporal convolution network for EEG-based motor imagery classification.

Neuroscience Aug 3, 2024
Brain-computer interface (BCI) is a technology that directly connects signals between the human brain and a computer or other external device. Motor imagery electroencephalographic (MI-EEG) signals are considered a promising paradigm for BCI systems,...
Electroencephalography Humans Brain-Computer Interfaces Imagination Neural Networks, Computer Brain
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Toward calibration-free motor imagery brain-computer interfaces: a VGG-based convolutional neural network and WGAN approach.

Journal of neural engineering Jul 31, 2024
Motor imagery (MI) represents one major paradigm of Brain-computer interfaces (BCIs) in which users rely on their electroencephalogram (EEG) signals to control the movement of objects. However, due to the inter-subject variability, MI BCIs require re...
Humans Brain-Computer Interfaces Movement Neural Networks, Computer Deep Learning Young Adult Imagination Female Electroencephalography Adult Calibration Male
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Temporal-spatial cross attention network for recognizing imagined characters.

Scientific reports Jul 4, 2024
Previous research has primarily employed deep learning models such as Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) for decoding imagined character signals. These approaches have treated the temporal and spatial features ...
Deep Learning Electroencephalography Signal Processing, Computer-Assisted Attention Brain-Computer Interfaces Imagination Humans Neural Networks, Computer Brain
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