AIMC Topic: Electroencephalography

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EEG based Classification of Long-term Stress Using Psychological Labeling.

Sensors (Basel, Switzerland) Mar 29, 2020
Stress research is a rapidly emerging area in the field of electroencephalography (EEG) signal processing. The use of EEG as an objective measure for cost effective and personalized stress management becomes important in situations like the nonavaila...
Humans Brain-Computer Interfaces Machine Learning Support Vector Machine Electroencephalography Adult Signal Processing, Computer-Assisted Male Stress, Psychological Algorithms Female Young Adult
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Deep Neural Oracles for Short-Window Optimized Compressed Sensing of Biosignals.

IEEE transactions on biomedical circuits and systems Mar 23, 2020
The recovery of sparse signals given their linear mapping on lower-dimensional spaces can be partitioned into a support estimation phase and a coefficient estimation phase. We propose to estimate the support with an oracle based on a deep neural netw...
Electroencephalography Signal Processing, Computer-Assisted Humans Heart Rate Neural Networks, Computer Brain Electrocardiography
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Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 18, 2020
Brain-machine interfaces (BMIs) can be used to decode brain activity into commands to control external devices. This paper presents the decoding of intuitive upper extremity imagery for multi-directional arm reaching tasks in three-dimensional (3D) e...
Robotics Electroencephalography Brain-Computer Interfaces Movement Humans Brain
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Automatic Seizure Detection using Fully Convolutional Nested LSTM.

International journal of neural systems Mar 16, 2020
The automatic seizure detection system can effectively help doctors to monitor and diagnose epilepsy thus reducing their workload. Many outstanding studies have given good results in the two-class seizure detection problems, but most of them are base...
Signal Processing, Computer-Assisted Sensitivity and Specificity Cerebral Cortex Deep Learning Models, Theoretical Electroencephalography Humans Seizures
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Challenge Accepted? Individual Performance Gains for Motor Imagery Practice with Humanoid Robotic EEG Neurofeedback.

Sensors (Basel, Switzerland) Mar 14, 2020
Optimizing neurofeedback (NF) and brain-computer interface (BCI) implementations constitutes a challenge across many fields and has so far been addressed by, among others, advancing signal processing methods or predicting the user's control ability f...
Humans Female Brain-Computer Interfaces Neurofeedback Imagery, Psychotherapy Young Adult Robotics Sensorimotor Cortex Adult Electroencephalography Male Signal Processing, Computer-Assisted
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Detection of Moderate Traumatic Brain Injury from Resting-State Eye-Closed Electroencephalography.

Computational intelligence and neuroscience Mar 11, 2020
Traumatic brain injury (TBI) is one of the injuries that can bring serious consequences if medical attention has been delayed. Commonly, analysis of computed tomography (CT) or magnetic resonance imaging (MRI) is required to determine the severity of...
Male Middle Aged Adolescent Electroencephalography Signal Processing, Computer-Assisted Humans Brain Concussion Aged Neural Networks, Computer Young Adult Female Adult
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Double-Criteria Active Learning for Multiclass Brain-Computer Interfaces.

Computational intelligence and neuroscience Mar 10, 2020
Recent technological advances have enabled researchers to collect large amounts of electroencephalography (EEG) signals in labeled and unlabeled datasets. It is expensive and time consuming to collect labeled EEG data for use in brain-computer interf...
Brain-Computer Interfaces Humans Machine Learning Electroencephalography
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Molecular and DNA Artificial Neural Networks via Fractional Coding.

IEEE transactions on biomedical circuits and systems Mar 9, 2020
This article considers implementation of artificial neural networks (ANNs) using molecular computing and DNA based on fractional coding. Prior work had addressed molecular two-layer ANNs with binary inputs and arbitrary weights. In prior work using f...
Humans Neural Networks, Computer Machine Learning Seizures Algorithms Stochastic Processes Signal Processing, Computer-Assisted DNA Computers, Molecular Electroencephalography
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Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control.

Communications biology Mar 9, 2020
Efficient action control is indispensable for goal-directed behaviour. Different theories have stressed the importance of either attention or response selection sub-processes for action control. Yet, it is unclear to what extent these processes can b...
Predictive Value of Tests Electroencephalography Signal Processing, Computer-Assisted Adolescent Cognition Support Vector Machine Brain Waves Neuropsychological Tests Motor Activity Reaction Time Attention Goals Brain Female Young Adult Adult Male Deep Learning Humans Conflict, Psychological
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An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding.

Scientific reports Mar 9, 2020
Previous studies of Brain Computer Interfaces (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinematics for lower limb movements during walking. In this computational study, we investigated offline dec...
Gait Brain-Computer Interfaces Machine Learning Algorithms Humans Electroencephalography Neural Networks, Computer
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