AIMC Topic: Electroencephalography
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Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques.
Australasian physical & engineering sciences in medicine
Feb 4, 2015
This paper describes a discrete wavelet transform-based feature extraction scheme for the classification of EEG signals. In this scheme, the discrete wavelet transform is applied on EEG signals and the relative wavelet energy is calculated in terms o...
Rapid automated classification of anesthetic depth levels using GPU based parallelization of neural networks.
Journal of medical systems
Feb 4, 2015
The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is ...
Automatic epileptic seizure detection using scalp EEG and advanced artificial intelligence techniques.
BioMed research international
Jan 29, 2015
The epilepsies are a heterogeneous group of neurological disorders and syndromes characterised by recurrent, involuntary, paroxysmal seizure activity, which is often associated with a clinicoelectrical correlate on the electroencephalogram. The diagn...
Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.
Journal of neuroscience methods
Jan 25, 2015
BACKGROUND: Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are prom...
Attentional Enhancement of Auditory Mismatch Responses: a DCM/MEG Study.
Cerebral cortex (New York, N.Y. : 1991)
Jan 16, 2015
Despite similar behavioral effects, attention and expectation influence evoked responses differently: Attention typically enhances event-related responses, whereas expectation reduces them. This dissociation has been reconciled under predictive codin...
A Novel Method for Automated Diagnosis of Epilepsy Using Complex-Valued Classifiers.
IEEE journal of biomedical and health informatics
Jan 6, 2015
The study reported herein proposes a new method for the diagnosis of epilepsy from electroencephalography (EEG) signals based on complex classifiers. To carry out this study, first the features of EEG data are extracted using a dual-tree complex wave...
Development of electroencephalographic pattern classifiers for real and imaginary thumb and index finger movements of one hand.
Artificial intelligence in medicine
Dec 18, 2014
OBJECTIVE: This study aimed to find effective approaches to electroencephalographic (EEG) signal analysis and resolve problems of real and imaginary finger movement pattern recognition and categorization for one hand.
Kernel collaborative representation-based automatic seizure detection in intracranial EEG.
International journal of neural systems
Dec 17, 2014
Automatic seizure detection is of great significance in the monitoring and diagnosis of epilepsy. In this study, a novel method is proposed for automatic seizure detection in intracranial electroencephalogram (iEEG) recordings based on kernel collabo...
Bridging the gap between motor imagery and motor execution with a brain-robot interface.
NeuroImage
Dec 17, 2014
According to electrophysiological studies motor imagery and motor execution are associated with perturbations of brain oscillations over spatially similar cortical areas. By contrast, neuroimaging and lesion studies suggest that at least partially di...
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...
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