AIMC Topic: Electroencephalography
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Deep Learning Meets Biomedical Ontologies: Knowledge Embeddings for Epilepsy.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 16, 2018
While biomedical ontologies have traditionally been used to guide the identification of concepts or relations in biomedical data, recent advances in deep learning are able to capture high-quality knowledge from textual data and represent it in graphi...
Inferring Clinical Correlations from EEG Reports with Deep Neural Learning.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 16, 2018
Successful diagnosis and management of neurological dysfunction relies on proper communication between the neurologist and the primary physician (or other specialists). Because this communication is documented within medical records, the ability to a...
Control of a 7-DOF Robotic Arm System With an SSVEP-Based BCI.
International journal of neural systems
Apr 12, 2018
Although robot technology has been successfully used to empower people who suffer from motor disabilities to increase their interaction with their physical environment, it remains a challenge for individuals with severe motor impairment, who do not h...
A Novel Method of Building Functional Brain Network Using Deep Learning Algorithm with Application in Proficiency Detection.
International journal of neural systems
Apr 11, 2018
Functional brain network (FBN) has become very popular to analyze the interaction between cortical regions in the last decade. But researchers always spend a long time to search the best way to compute FBN for their specific studies. The purpose of t...
Deep learning for healthcare applications based on physiological signals: A review.
Computer methods and programs in biomedicine
Apr 11, 2018
BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.20...
A Machine Learning Approach to the Detection of Pilot's Reaction to Unexpected Events Based on EEG Signals.
Computational intelligence and neuroscience
Apr 10, 2018
This work considers the problem of utilizing electroencephalographic signals for use in systems designed for monitoring and enhancing the performance of aircraft pilots. Systems with such capabilities are generally referred to as cognitive cockpits. ...
Motor Imagery-Based Brain-Computer Interface Coupled to a Robotic Hand Orthosis Aimed for Neurorehabilitation of Stroke Patients.
Journal of healthcare engineering
Apr 3, 2018
Motor imagery-based brain-computer interfaces (BCI) have shown potential for the rehabilitation of stroke patients; however, low performance has restricted their application in clinical environments. Therefore, this work presents the implementation o...
Neonatal Seizure Detection Using Deep Convolutional Neural Networks.
International journal of neural systems
Apr 2, 2018
Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not ...
Resting-state functional connectivity predicts the ability to adapt arm reaching in a robot-mediated force field.
NeuroImage
Mar 26, 2018
Motor deficits are common outcomes of neurological conditions such as stroke. In order to design personalised motor rehabilitation programmes such as robot-assisted therapy, it would be advantageous to predict how a patient might respond to such trea...
Ongoing brain rhythms shape I-wave properties in a computational model.
Brain stimulation
Mar 20, 2018
BACKGROUND: Responses to transcranial magnetic stimulation (TMS) are notoriously variable. Previous studies have observed a dependence of TMS-induced responses on ongoing brain activity, for instance sensorimotor rhythms. This suggests an opportunity...
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