AIMC Topic: Electroencephalography

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Machine learning on encephalographic activity may predict opioid analgesia.

European journal of pain (London, England) Jun 11, 2015
BACKGROUND: Opioids are used for the treatment of pain. However, 30-50% of patients have insufficient effect to the opioid initially selected by the physician, and there is an urgent need for biomarkers to select responders to the most appropriate dr...
Young Adult Adult Male Middle Aged Support Vector Machine Electroencephalography Analgesics, Opioid Morphine Humans Female Pain
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Multimodal predictor of neurodevelopmental outcome in newborns with hypoxic-ischaemic encephalopathy.

Computers in biology and medicine Jun 10, 2015
Automated multimodal prediction of outcome in newborns with hypoxic-ischaemic encephalopathy is investigated in this work. Routine clinical measures and 1h EEG and ECG recordings 24h after birth were obtained from 38 newborns with different grades of...
Infant, Newborn, Diseases Predictive Value of Tests Electroencephalography Hypoxia-Ischemia, Brain Humans Databases, Factual Female Infant, Newborn Male Electrocardiography Support Vector Machine
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Incorporating advanced language models into the P300 speller using particle filtering.

Journal of neural engineering Jun 10, 2015
OBJECTIVE: The P300 speller is a common brain-computer interface (BCI) application designed to communicate language by detecting event related potentials in a subject's electroencephalogram signal. Information about the structure of natural language ...
Humans Machine Learning Algorithms Computer Simulation Pattern Recognition, Automated Brain-Computer Interfaces Task Performance and Analysis Event-Related Potentials, P300 Communication Devices for People with Disabilities Reproducibility of Results Brain Mapping Word Processing Natural Language Processing Sensitivity and Specificity Electroencephalography Models, Statistical Signal Processing, Computer-Assisted
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Extracting latent brain states--Towards true labels in cognitive neuroscience experiments.

NeuroImage Jun 9, 2015
Neuroscientific data is typically analyzed based on the behavioral response of the participant. However, the errors made may or may not be in line with the neural processing. In particular in experiments with time pressure or studies where the thresh...
Adult Male Unsupervised Machine Learning Electroencephalography Brain Female Young Adult Attention Cognitive Neuroscience Evoked Potentials Pattern Recognition, Visual Humans
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EMD-Based Temporal and Spectral Features for the Classification of EEG Signals Using Supervised Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 8, 2015
This paper presents a novel method for feature extraction from electroencephalogram (EEG) signals using empirical mode decomposition (EMD). Its use is motivated by the fact that the EMD gives an effective time-frequency analysis of nonstationary sign...
Sensitivity and Specificity Spatio-Temporal Analysis Diagnosis, Computer-Assisted Electroencephalography Epilepsy Supervised Machine Learning Pattern Recognition, Automated Humans Algorithms Reproducibility of Results
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Grading hypoxic-ischemic encephalopathy severity in neonatal EEG using GMM supervectors and the support vector machine.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Jun 3, 2015
OBJECTIVE: This work presents a novel automated system to classify the severity of hypoxic-ischemic encephalopathy (HIE) in neonates using EEG.
Hypoxia-Ischemia, Brain Humans Infant, Newborn Female Male Support Vector Machine Electroencephalography
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Control of a Wheelchair in an Indoor Environment Based on a Brain-Computer Interface and Automated Navigation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 1, 2015
The concept of controlling a wheelchair using brain signals is promising. However, the continuous control of a wheelchair based on unstable and noisy electroencephalogram signals is unreliable and generates a significant mental burden for the user. A...
Sensitivity and Specificity Male Ecosystem Robotics Humans Equipment Failure Analysis Female Electroencephalography Machine Learning Reproducibility of Results Man-Machine Systems Equipment Design Young Adult Wheelchairs Pattern Recognition, Automated Adult Spatial Navigation Brain-Computer Interfaces
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A Fuzzy-Based Fusion Method of Multimodal Sensor-Based Measurements for the Quantitative Evaluation of Eye Fatigue on 3D Displays.

Sensors (Basel, Switzerland) May 7, 2015
With the rapid increase of 3-dimensional (3D) content, considerable research related to the 3D human factor has been undertaken for quantitatively evaluating visual discomfort, including eye fatigue and dizziness, caused by viewing 3D content. Variou...
Face Body Temperature Blinking Scalp Equipment Design Signal Processing, Computer-Assisted Electrodes Asthenopia Humans Male Female Young Adult Imaging, Three-Dimensional Adult Fuzzy Logic Electroencephalography
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On the proper selection of preictal period for seizure prediction.

Epilepsy & behavior : E&B May 3, 2015
Supervised machine learning-based seizure prediction methods consider preictal period as an important prerequisite parameter during training. However, the exact length of the preictal state is unclear and varies from seizure to seizure. We propose a ...
Electroencephalography Seizures Adolescent Time Factors Child Young Adult Adult Humans Male Machine Learning Middle Aged Female
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A neural network-based optimal spatial filter design method for motor imagery classification.

PloS one May 1, 2015
In this study, a novel spatial filter design method is introduced. Spatial filtering is an important processing step for feature extraction in motor imagery-based brain-computer interfaces. This paper introduces a new motor imagery signal classificat...
Humans Electroencephalography Neural Networks, Computer Brain-Computer Interfaces Algorithms Motor Activity Imagery, Psychotherapy
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