AIMC Topic: Electroencephalography
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Ten-dimensional anthropomorphic arm control in a human brain-machine interface: difficulties, solutions, and limitations.
Journal of neural engineering
Dec 16, 2014
OBJECTIVE: In a previous study we demonstrated continuous translation, orientation and one-dimensional grasping control of a prosthetic limb (seven degrees of freedom) by a human subject with tetraplegia using a brain-machine interface (BMI). The cur...
Determining the appropriate amount of anesthetic gas using DWT and EMD combined with neural network.
Journal of medical systems
Dec 4, 2014
The spectrum of EEG has been studied to predict the depth of anesthesia using variety of signal processing methods up to date. Those standard models have used the full spectrum of EEG signals together with the systolic-diastolic pressure and pulse va...
An SSVEP-Based Brain-Computer Interface for Text Spelling With Adaptive Queries That Maximize Information Gain Rates.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dec 2, 2014
This paper presents a brain-computer interface for text entry using steady-state visually evoked potentials (SSVEP). Like other SSVEP-based spellers, ours identifies the desired input character by posing questions (or queries) to users through a visu...
Reproducibility of Results
Young Adult
Sensitivity and Specificity
Male
Adolescent
Humans
Machine Learning
Female
Pattern Recognition, Automated
Child
Brain-Computer Interfaces
Natural Language Processing
Evoked Potentials, Visual
Electroencephalography
Communication Devices for People with Disabilities
Information Storage and Retrieval
Word Processing
A novel EOG/EEG hybrid human-machine interface adopting eye movements and ERPs: application to robot control.
IEEE transactions on bio-medical engineering
Nov 12, 2014
This study presents a novel human-machine interface (HMI) based on both electrooculography (EOG) and electroencephalography (EEG). This hybrid interface works in two modes: an EOG mode recognizes eye movements such as blinks, and an EEG mode detects ...
Using Relevance Feedback to Distinguish the Changes in EEG During Different Absence Seizure Phases.
Clinical EEG and neuroscience
Sep 21, 2014
We carried out a series of statistical experiments to explore the utility of using relevance feedback on electroencephalogram (EEG) data to distinguish between different activity states in human absence epilepsy. EEG recordings from 10 patients with ...
Electroencephalographic Changes of Brain Oscillatory Activity After Upper Limb Somatic Sensation Training in a Patient With Somatosensory Deficit After Stroke.
Clinical EEG and neuroscience
Sep 2, 2014
The development of an innovative functional assessment procedure based on the combination of electroencephalography (EEG) and robot-assisted upper limb devices may provide new insights into the dynamics of cortical reorganization promoted by rehabili...
A machine learning approach using auditory odd-ball responses to investigate the effect of Clozapine therapy.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Aug 27, 2014
OBJECTIVE: To develop a machine learning (ML) methodology based on features extracted from odd-ball auditory evoked potentials to identify neurophysiologic changes induced by Clozapine (CLZ) treatment in responding schizophrenic (SCZ) subjects. This ...
Epileptic seizure prediction using relative spectral power features.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jun 4, 2014
OBJECTIVE: Prediction of epileptic seizures can improve the living conditions for refractory epilepsy patients. We aimed to improve sensitivity and specificity of prediction methods, and to reduce the number of false alarms.
Time-frequency modulation of ERD and EEG coherence in robot-assisted hand performance.
Brain topography
May 17, 2014
A better understanding of cortical modifications related to movement preparation and execution after robot-assisted training could aid in refining rehabilitation therapy protocols for stroke patients. Electroencephalography (EEG) modifications of cor...
Decoding objects of basic categories from electroencephalographic signals using wavelet transform and support vector machines.
Brain topography
May 17, 2014
Decoding and classification of objects through task-oriented electroencephalographic (EEG) signals are the most crucial goals of recent researches conducted mainly for brain-computer interface applications. In this study we aimed to classify single-t...
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