AIMC Topic: Imagery, Psychotherapy

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A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke.

Clinical EEG and neuroscience Apr 21, 2014
Electroencephalography (EEG)-based motor imagery (MI) brain-computer interface (BCI) technology has the potential to restore motor function by inducing activity-dependent brain plasticity. The purpose of this study was to investigate the efficacy of ...
Imagery, Psychotherapy Robotics Electroencephalography Recovery of Function Physical Therapy Modalities Stroke Rehabilitation Middle Aged Brain-Computer Interfaces Treatment Outcome Upper Extremity Adult Humans Male Female Aged
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A Deep Learning Framework Based on Dynamic Channel Selection for Early Classification of Left and Right Hand Motor Imagery Tasks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Ideal brain-computer interfaces (BCIs) need to be efficient and accurate, demanding for classifiers that can work across subjects while providing high classification accu-racy results from recordings with short duration. To address this problem, we p...
Brain-Computer Interfaces Imagery, Psychotherapy Humans Neural Networks, Computer Deep Learning Hand
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A Pruned Deep Learning Approach for Classification of Motor Imagery Electroencephalography Signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
The Deep Learning (DL) approach has been gaining much popularity in recent years in the development of electroencephalogram (EEG) based Motor Imagery (MI) Brain-Computer Interface (BCI) systems, aiming to improve the performance of existing stroke re...
Humans Neural Networks, Computer Electroencephalography Imagery, Psychotherapy Algorithms Deep Learning
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Generating Hyperspectral Skin Cancer Imagery using Generative Adversarial Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
In this study we develop a proof of concept of using generative adversarial neural networks in hyperspectral skin cancer imagery production. Generative adversarial neural network is a neural network, where two neural networks compete. The generator t...
Neural Networks, Computer Machine Learning Humans Skin Neoplasms Learning Imagery, Psychotherapy
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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 Jul 1, 2019
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...
Brain-Computer Interfaces Imagination Electroencephalography Imagery, Psychotherapy Humans Neural Networks, Computer Algorithms Deep Learning
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EEG Processing to Discriminate Transitive-Intransitive Motor Imagery Tasks: Preliminary Evidences using Support Vector Machines.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
It is known that brain dynamics significantly changes during motor imagery tasks of upper limb involving different kind of interactions with an object. Nevertheless, an automatic discrimination of transitive (i.e., actions involving an object) and in...
Electroencephalography Movement Imagery, Psychotherapy Gestures Support Vector Machine
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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 Jul 1, 2018
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...
Neural Networks, Computer Imagination Electroencephalography Algorithms Brain-Computer Interfaces Imagery, Psychotherapy Deep Learning
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Increasing the learning Capacity of BCI Systems via CNN-HMM models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Despite all the work in the Brain Computer Interface (BCI) community, one of the main issues that prevents it from becoming pervasive is the limitation on the number of commands with a satisfactory accuracy of detection. In this paper, we propose a s...
Brain-Computer Interfaces Imagery, Psychotherapy Machine Learning Humans Neural Networks, Computer
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