AIMC Topic: Electroencephalography

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Epileptic seizure detection in EEG signal using machine learning techniques.

Australasian physical & engineering sciences in medicine Dec 20, 2017
Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are ti...
Epilepsy Humans Seizures Machine Learning Signal Processing, Computer-Assisted Support Vector Machine Principal Component Analysis Electroencephalography
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Epileptic Seizures Prediction Using Machine Learning Methods.

Computational and mathematical methods in medicine Dec 19, 2017
Epileptic seizures occur due to disorder in brain functionality which can affect patient's health. Prediction of epileptic seizures before the beginning of the onset is quite useful for preventing the seizure by medication. Machine learning technique...
Models, Statistical Electroencephalography Epilepsy Reproducibility of Results Seizures Humans Sensitivity and Specificity Signal Processing, Computer-Assisted Algorithms Diagnosis, Computer-Assisted Brain Support Vector Machine
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Epileptic seizure detection using DWT-based approximate entropy, Shannon entropy and support vector machine: a case study.

Journal of medical engineering & technology Dec 18, 2017
In this work, we have used a time-frequency domain analysis method called discrete wavelet transform (DWT) technique. This method stand out compared to other proposed methods because of its algorithmic elegance and accuracy. A wavelet is a mathematic...
Algorithms Support Vector Machine Electroencephalography Epilepsy Humans Wavelet Analysis Entropy
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Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction.

Scientific reports Dec 14, 2017
Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, ...
Male Robotics Electroencephalography Evoked Potentials Humans Female Reinforcement, Psychology Feedback, Psychological
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Modeling spike-wave discharges by a complex network of neuronal oscillators.

Neural networks : the official journal of the International Neural Network Society Dec 13, 2017
PURPOSE: The organization of neural networks and the mechanisms, which generate the highly stereotypical for absence epilepsy spike-wave discharges (SWDs) is heavily debated. Here we describe such a model which can both reproduce the characteristics ...
Somatosensory Cortex Epilepsy, Absence Animals Disease Models, Animal Action Potentials Electroencephalography Seizures Neurons Thalamus Humans Neural Networks, Computer Brain
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Bullying incidences identification within an immersive environment using HD EEG-based analysis: A Swarm Decomposition and Deep Learning approach.

Scientific reports Dec 11, 2017
Bullying is an everlasting phenomenon and the first, yet difficult, step towards the solution is its detection. Conventional approaches for bullying incidence identification include questionnaires, conversations and psychological tests. Here, unlike ...
Young Adult Adult Male Deep Learning Virtual Reality Neural Networks, Computer Incidence Brain Electroencephalography Humans Computer Simulation Bullying Female
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Exploring the Organization of Semantic Memory through Unsupervised Analysis of Event-related Potentials.

Journal of cognitive neuroscience Dec 6, 2017
Modern multivariate methods have enabled the application of unsupervised techniques to analyze neurophysiological data without strict adherence to predefined experimental conditions. We demonstrate a multivariate method that leverages priming effects...
Female Young Adult Adult Male Humans Algorithms Brain Signal Processing, Computer-Assisted Semantics Memory Evoked Potentials Middle Aged Cluster Analysis Unsupervised Machine Learning Electroencephalography
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An EEG-based functional connectivity measure for automatic detection of alcohol use disorder.

Artificial intelligence in medicine Nov 21, 2017
BACKGROUND: The abnormal alcohol consumption could cause toxicity and could alter the human brain's structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and m...
Reproducibility of Results Aged Adult Male Middle Aged Case-Control Studies Diagnosis, Computer-Assisted Humans Brain Female Signal Processing, Computer-Assisted Automation Alcoholism Brain Waves ROC Curve Predictive Value of Tests Logistic Models Area Under Curve Support Vector Machine Bayes Theorem Electroencephalography
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Sequential Probability Ratio Testing with Power Projective Base Method Improves Decision-Making for BCI.

Computational and mathematical methods in medicine Nov 14, 2017
Obtaining a fast and reliable decision is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this study, the EEG signals were firstly analyzed with...
Wheelchairs Brain-Computer Interfaces Movement Humans Motor Activity Bayes Theorem Machine Learning Electroencephalography Algorithms Signal Processing, Computer-Assisted Reproducibility of Results Probability Decision Making
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Mathematic Network of Seizure Activity: How Presurgical Simulation Can Predict Postsurgical Success.

World neurosurgery Nov 11, 2017
Mathematical Computing Electroencephalography Humans Epilepsy Neural Networks, Computer Preoperative Care Computer Simulation Treatment Outcome
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