AIMC Topic: Electroencephalography

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[Study on Sleep Staging Methods Based on Heart Rate Variability Analysis].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Jun 1, 2016
In order to realize sleep staging automatically and conveniently,we used support vector machine(SVM)to analyze the correlation between heart rate variability and sleep stage experimentally.R-R intervals(RRIs)from 33 cases of sleep clinical data of Ti...
Electroencephalography Heart Rate Polysomnography Sleep Stages Humans Support Vector Machine Principal Component Analysis
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Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations.

The Journal of neuroscience : the official journal of the Society for Neuroscience Apr 13, 2016
UNLABELLED: Sleep is critical for regulation of synaptic efficacy, memories, and learning. However, the underlying mechanisms of how sleep rhythms contribute to consolidating memories acquired during wakefulness remain unclear. Here we studied the ro...
Calcium Channels Cerebral Cortex Memory Thalamus Neurons Synapses Sleep Sodium Channels Humans Neural Networks, Computer Algorithms Computer Simulation Neuronal Plasticity Models, Neurological Electroencephalography
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[Recognition of Low Arousal Level Electroencephalogram in the Vigilance Based on Wavelet Packet Rhythm and Support Vector Machine].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 1, 2016
Poor and monotonous work could easily lead to a decrease of arousal level of the monitoring work personnel. In order to improve the performance of monitoring work, low arousal level needs to be recognized and awakened. We proposed a recognition metho...
Electroencephalography Signal Processing, Computer-Assisted Wavelet Analysis Arousal Humans Brain Support Vector Machine
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Electroencephalographic markers of robot-aided therapy in stroke patients for the evaluation of upper limb rehabilitation.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation Dec 1, 2015
Stroke is the leading cause of permanent disability in developed countries; its effects may include sensory, motor, and cognitive impairment as well as a reduced ability to perform self-care and participate in social and community activities. A numbe...
Neuronal Plasticity Robotics Electroencephalography Signal Processing, Computer-Assisted Male Middle Aged Follow-Up Studies Cerebral Cortex Therapy, Computer-Assisted Paresis Stroke Rehabilitation Electromyography Stroke Arm Humans Female Aged Biomechanical Phenomena
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Support vector machines using EEG features of cross-frequency coupling can predict treatment outcome in Mecp2-deficient mice.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2015
Anti-convulsive drug treatments of epilepsy typically produce varied outcomes from one patient to the next, often necessitating patients to go through several anticonvulsive drug trials until an appropriate treatment is found. The focus of this study...
Support Vector Machine Electroencephalography Methyl-CpG-Binding Protein 2 Rett Syndrome Animals Mice Treatment Outcome
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Optimized echo state networks with leaky integrator neurons for EEG-based microsleep detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2015
The performance of a microsleep detection system was calculated in terms of its ability to detect the behavioural microsleep state (1-s epochs) from spectral features derived from 16-channel EEG sampled at 256 Hz. Best performance from a single class...
Electroencephalography Signal Processing, Computer-Assisted Sleep Humans Neural Networks, Computer Young Adult Adult Male Adolescent Discriminant Analysis
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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 Aug 1, 2015
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...
Humans Female Aged Models, Theoretical Hand Brain-Computer Interfaces Electrocorticography Imagination Robotics Electroencephalography Equipment Design
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EEG error potentials detection and classification using time-frequency features for robot reinforcement learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2015
In thought-based steering of robots, error potentials (ErrP) can appear when the action resulting from the brain-machine interface (BMI) classifier/controller does not correspond to the user's thought. Using the Steady State Visual Evoked Potentials ...
Electroencephalography Brain-Computer Interfaces Evoked Potentials, Visual Humans Models, Theoretical Robotics
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Emotion recognition from sound stimuli based on back-propagation neural networks and electroencephalograms.

The Journal of the Acoustical Society of America Aug 1, 2015
This research aims to explore the feasibility of using back-propagation (BP) neural networks and electroencephalograms (EEGs) to recognize the emotional reactions induced by sound stimuli in the dimensions of pleasure and arousal, as well as compare ...
Neural Networks, Computer Female Young Adult Adult Male Adolescent Emotions Humans Models, Psychological Arousal Self-Assessment Feasibility Studies Pleasure Pattern Recognition, Automated Acoustic Stimulation Models, Neurological Electroencephalography Personal Satisfaction
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Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy.

Chaos (Woodbury, N.Y.) Aug 1, 2015
In this paper, experimental neurophysiologic recording and statistical analysis are combined to investigate the nonlinear characteristic and the cognitive function of the brain. Fuzzy approximate entropy and fuzzy sample entropy are applied to charac...
Alzheimer Disease Entropy Alpha Rhythm Models, Neurological Electroencephalography Signal Processing, Computer-Assisted Electrodes Male Case-Control Studies Fuzzy Logic Humans Brain Female Aged
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