AIMC Topic: Electroencephalography

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Classification of Movement Direction From Electroencephalogram During Working Memory Time.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
When humans perform cognitive tasks, it is necessary to hold information temporarily. This is done by a brain function called working memory (WM). Since WM is active during the whole time range from stimulus presentation to task execution, onset dete...

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...

Multimodal Emotion Recognition from Eye Image, Eye Movement and EEG Using Deep Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In consideration of the complexity of recording electroencephalography(EEG), some researchers are trying to find new features of emotion recognition. In order to investigate the potential of eye tracking glasses for multimodal emotion recognition, we...

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...

SLES: A Novel CNN-based Method for Sensor Reduction in P300 Speller.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A Brain Computer Interface (BCI) character speller allows human-beings to directly spell characters using eye-gazes, thereby building communication between the human brain and a computer. Current popular BCI character speller systems employ a large n...

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 ...

Novel Automatic Epilepsy Detection Method Multi-weight Transition Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The automatic diagnosis of epilepsy using Electroencephalogram (EEG) signals had always been an important research direction. A novel automatic epilepsy detection method based on multi-weight transition network was proposed in this paper. The epilept...

A convolutional neural network based framework for classification of seizure types.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Epileptic seizures are caused by a disturbance in the electrical activity of the brain and classified as many different types of epileptic seizures based on the characteristics of EEG and other parameters. Till now research has been conducted to clas...

Epileptic States Recognition Using Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic recognition of electroencephalogram (EEG) signals plays a major role in epilepsy diagnosis and assessment. However, the recognition accuracy of conventional methods is usually not satisfactory because of the inconsistent distribution of tra...