AIMC Topic: Imagination

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Classification and Transfer Learning of EEG during a Kinesthetic Motor Imagery Task using Deep Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The reliable classification of Electroencephalography (EEG) signals is a crucial step towards making EEG-controlled non-invasive neuro-exoskeleton rehabilitation a practical reality. EEG signals collected during motor imagery tasks have been proposed...

Reconstructing Degree of Forearm Rotation from Imagined movements for BCI-based Robot Hand Control.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Brain-computer interface (BCI) is an important tool for rehabilitation and control of an external device (e.g., robot arm or home appliances). Fully reconstruction of upper limb movement from brain signals is one of the critical issues for intuitive ...

Imagine how to behave: the influence of imagined contact on human-robot interaction.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Imagined contact (IC), that is, mentally simulating an interaction with an outgroup member, reduces negative attitudes towards outgroup members, increases contact intentions, and reduces intergroup anxiety in human-human intergroup context. Our exper...

DeepMI: Deep Learning for Multiclass Motor Imagery Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In Brain-Computer Interface (BCI) Research,Electroencephalography (EEG) has obtained great attention for biomedical applications. In BCI system, feature representation and classification are important tasks as the accuracy of classification highly de...

Classification of electroencephalogram signals using wavelet-CSP and projection extreme learning machine.

The Review of scientific instruments
Brain-computer interface (BCI) systems establish a direct communication channel from the brain to an output device. As the basis of BCIs, recognizing motor imagery activities poses a considerable challenge to signal processing due to the complex and ...

Inferring imagined speech using EEG signals: a new approach using Riemannian manifold features.

Journal of neural engineering
OBJECTIVE: In this paper, we investigate the suitability of imagined speech for brain-computer interface (BCI) applications.

Smooth leader or sharp follower? Playing the mirror game with a robot.

Restorative neurology and neuroscience
BACKGROUND: The increasing number of opportunities for human-robot interactions in various settings, from industry through home use to rehabilitation, creates a need to understand how to best personalize human-robot interactions to fit both the user ...

Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a practical and convenient non-linear classifier.

Biomedizinische Technik. Biomedical engineering
There is general agreement in the brain-computer interface (BCI) community that although non-linear classifiers can provide better results in some cases, linear classifiers are preferable. Particularly, as non-linear classifiers often involve a numbe...

The importance of imagination (or lack thereof) in artificial, human and quantum decision making.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Enlarging upon experiments and analysis that I did jointly some years ago, in which artificial (symbolic, neural-net and pattern) learning and generalization were compared with that of humans, I will emphasize the role of imagination (or lack thereof...

Online control of a humanoid robot through hand movement imagination using CSP and ECoG based features.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Intention recognition through decoding brain activity could lead to a powerful and independent Brain-Computer-Interface (BCI) allowing for intuitive control of devices like robots. A common strategy for realizing such a system is the motor imagery (M...