AIMC Topic: Electroencephalography

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The Current Research Landscape on the Artificial Intelligence Application in the Management of Depressive Disorders: A Bibliometric Analysis.

International journal of environmental research and public health Jun 18, 2019
Artificial intelligence (AI)-based techniques have been widely applied in depression research and treatment. Nonetheless, there is currently no systematic review or bibliometric analysis in the medical literature about the applications of AI in depre...
Electroencephalography Depressive Disorder Humans Artificial Intelligence Depression Bibliometrics
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Weighted Transfer Learning for Improving Motor Imagery-Based Brain-Computer Interface.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 17, 2019
One of the major limitations of motor imagery (MI)-based brain-computer interface (BCI) is its long calibration time. Due to between sessions/subjects variations in the properties of brain signals, typically, a large amount of training data needs to ...
Movement Space Perception Imagination Healthy Volunteers Psychomotor Performance Humans Calibration Machine Learning Brain-Computer Interfaces Algorithms Electroencephalography
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Deep convolutional neural network for classification of sleep stages from single-channel EEG signals.

Journal of neuroscience methods Jun 12, 2019
Using a smart method for automatic diagnosis in medical applications, such as sleep stage classification is considered as one of the important challenges of the last few years which can replace the time-consuming process of visual inspection done by ...
Humans Signal Processing, Computer-Assisted Deep Learning Electroencephalography Sleep Stages
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Sleep stage classification using covariance features of multi-channel physiological signals on Riemannian manifolds.

Computer methods and programs in biomedicine Jun 10, 2019
BACKGROUND AND OBJECTIVE: The recognition of many sleep related pathologies highly relies on an accurate classification of sleep stages. Clinically, sleep stages are usually labelled by sleep experts through visually inspecting the whole-night polyso...
Sleep Humans Data Interpretation, Statistical Machine Learning Polysomnography Electroencephalography Algorithms Electrooculography Signal Processing, Computer-Assisted Databases, Factual Sleep Stages Computer Simulation Reproducibility of Results
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Design and Implementation of a Machine Learning Based EEG Processor for Accurate Estimation of Depth of Anesthesia.

IEEE transactions on biomedical circuits and systems Jun 10, 2019
Accurate monitoring of the depth of anesthesia (DoA) is essential for intraoperative and postoperative patient's health. Commercially available electroencephalograph (EEG)-based DoA monitors are recommended only for certain anesthetic drugs and speci...
Fourier Analysis Electroencephalography Equipment Design Anesthesia Humans Machine Learning Algorithms Aged Adult Middle Aged ROC Curve
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Slow cortical potential signal classification using concave-convex feature.

Journal of neuroscience methods Jun 8, 2019
BACKGROUND: The classification of the slow cortical potential (SCP) signals plays a key role in a variety of research areas, including disease diagnostics, human-machine interaction, and education. The widely used classification methods, which combin...
Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted Young Adult Cerebral Cortex Adult Male Humans Female
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Using heart rate profiles during sleep as a biomarker of depression.

BMC psychiatry Jun 7, 2019
BACKGROUND: Abnormalities in heart rate during sleep linked to impaired neuro-cardiac modulation may provide new information about physiological sleep signatures of depression. This study assessed the validity of an algorithm using patterns of heart ...
Humans Machine Learning Retrospective Studies Adult Male Middle Aged Depression Female Aged Aged, 80 and over Young Adult Adolescent Heart Rate Electrocardiography Sleep Electroencephalography Polysomnography Sleep Wake Disorders
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Autoencoding of long-term scalp electroencephalogram to detect epileptic seizure for diagnosis support system.

Computers in biology and medicine Jun 5, 2019
INTRODUCTION: Epileptologists could benefit from a diagnosis support system that automatically detects seizures because visual inspection of long-term electroencephalograms (EEGs) is extremely time-consuming. However, the diversity of seizures among ...
Humans Female Adult Scalp Support Vector Machine Diagnosis, Computer-Assisted Male Electroencephalography Middle Aged Seizures Adolescent Signal Processing, Computer-Assisted Child
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Effects of Transcranial Direct Current Stimulation (tDCS) Combined With Wrist Robot-Assisted Rehabilitation on Motor Recovery in Subacute Stroke Patients: A Randomized Controlled Trial.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 3, 2019
Both transcranial direct current stimulation (tDCS) and wrist robot-assisted training have demonstrated to be promising approaches for stroke rehabilitation. However, the effects of the combination of the two treatments in subacute stroke patients ar...
Treatment Outcome Recovery of Function Robotics Single-Blind Method Male Middle Aged Adolescent Upper Extremity Humans Stroke Rehabilitation Algorithms Transcranial Direct Current Stimulation Female Motor Cortex Aged, 80 and over Aged Electroencephalography Young Adult Wrist Adult Combined Modality Therapy Biomechanical Phenomena Electrodes
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Arrangements of Resting State Electroencephalography as the Input to Convolutional Neural Network for Biometric Identification.

Computational intelligence and neuroscience Jun 2, 2019
Biometric is an important field that enables identification of an individual to access their sensitive information and asset. In recent years, electroencephalography- (EEG-) based biometrics have been popularly explored by researchers because EEG is ...
Algorithms Humans Biometric Identification Electroencephalography Neural Networks, Computer Signal Processing, Computer-Assisted Machine Learning Brain-Computer Interfaces
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