AIMC Topic: Imagination

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Classification of Motor Imagery Tasks Derived from Unilateral Upper Limb based on a Weight-optimized Learning Model.

Journal of integrative neuroscience
BACKGROUND: The accuracy of decoding fine motor imagery (MI) tasks remains relatively low due to the dense distribution of active areas in the cerebral cortex.

An Evaluation of Hybrid Deep Learning Models for Classifying Multiple Lower Limb Actions.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Brain-computer Interfaces (BCIs) interpret electroencephalography (EEG) signals and translate them into control commands for operating external devices. The motor imagery (MI) paradigm is popular in this context. Recent research has demonstrated that...

Classification of EEG signals related to real and imagery knee movements using deep learning for brain computer interfaces.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Non-invasive Brain-Computer Interface (BCI) uses an electroencephalogram (EEG) to obtain information on brain neural activity. Because EEG can be contaminated by various artifacts during the collection process, it has primarily evolved in...

The Enactive and Interactive Dimensions of AI: Ingenuity and Imagination Through the Lens of Art and Music.

Artificial life
Dualisms are pervasive. The divisions between the rational mind, the physical body, and the external natural world have set the stage for the successes and failures of contemporary cognitive science and artificial intelligence.1 Advanced machine lear...

Exploring differences for motor imagery using Teager energy operator-based EEG microstate analyses.

Journal of integrative neuroscience
In this paper, the differences between two motor imagery tasks are captured through microstate parameters (occurrence, duration and coverage, and mean spatial correlation (Mspatcorr)) derived from a novel method based on electroencephalogram microsta...

AI, visual imagery, and a case study on the challenges posed by human intelligence tests.

Proceedings of the National Academy of Sciences of the United States of America
Observations abound about the power of visual imagery in human intelligence, from how Nobel prize-winning physicists make their discoveries to how children understand bedtime stories. These observations raise an important question for cognitive scien...

Decoding spectro-temporal representation for motor imagery recognition using ECoG-based brain-computer interfaces.

Journal of integrative neuroscience
One of the challenges in brain-computer interface systems is obtaining motor imagery recognition from brain activities. Brain-signal decoding robustness and system performance improvement during the motor imagery process are two of the essential issu...

Tensor Discriminant Analysis for MI-EEG Signal Classification Using Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Motor Imagery (MI) is a typical paradigm for Brain-Computer Interface (BCI) system. In this paper, we propose a new framework by introducing a tensor-based feature representation of the data and also utilizing a convolutional neural network (CNN) arc...

Deep Learning of Motor Imagery EEG Classification for Brain-Computer Interface Illiterate Subject.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
BCI illiterate subject is defined as the subject who cannot achieve accuracy higher than 70%. BCI illiterate subject cannot produce stronger contralateral ERD/ERS activity, thus most of the frequency band-based algorithms cannot obtain higher accurac...

Improving The Performance of Motor Imagery Based Brain-Computer Interface Using Phase Space Reconstruction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In recent decades, motor imagery (MI) based brain-computer interface (BCI) is served as a control system or rehabilitation tool for motor disabled people. But it has limited applications because of its lower classification performance (classification...