AIMC Topic: Electroencephalography
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Single-Channel Real-Time Drowsiness Detection Based on Electroencephalography.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
The need of a reliable drowsiness detection system is arising today, as drowsiness is considered as a major cause for accidents as much as alcohol. In this paper, we propose a real-time drowsiness detection algorithm based on a single-channel electro...
Classification of electroencephalogram signals using wavelet-CSP and projection extreme learning machine.
The Review of scientific instruments
Jul 1, 2018
Brain-computer interface (BCI) systems establish a direct communication channel from the brain to an output device. As the basis of BCIs, recognizing motor imagery activities poses a considerable challenge to signal processing due to the complex and ...
A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 1, 2018
Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signa...
Brain-machine interfaces for controlling lower-limb powered robotic systems.
Journal of neural engineering
Apr 1, 2018
OBJECTIVE: Lower-limb, powered robotics systems such as exoskeletons and orthoses have emerged as novel robotic interventions to assist or rehabilitate people with walking disabilities. These devices are generally controlled by certain physical maneu...
A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems.
Journal of neural engineering
Apr 1, 2018
OBJECTIVE: Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-bas...
The combined use of virtual reality and EEG to study language processing in naturalistic environments.
Behavior research methods
Apr 1, 2018
When we comprehend language, we often do this in rich settings where we can use many cues to understand what someone is saying. However, it has traditionally been difficult to design experiments with rich three-dimensional contexts that resemble our ...
A Hybrid Network for ERP Detection and Analysis Based on Restricted Boltzmann Machine.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 1, 2018
Detecting and Please provide the correct one analyzing the event-related potential (ERP) remains an important problem in neuroscience. Due to the low signal-to-noise ratio and complex spatio-temporal patterns of ERP signals, conventional methods usua...
Robust Support Matrix Machine for Single Trial EEG Classification.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 1, 2018
Electroencephalogram (EEG) signals are of complex structure and can be naturally represented as matrices. Classification is one of the most important steps for EEG signal processing. Newly developed classifiers can handle these matrix-form data by ad...
Prediction of Bispectral Index during Target-controlled Infusion of Propofol and Remifentanil: A Deep Learning Approach.
Anesthesiology
Mar 1, 2018
BACKGROUND: The discrepancy between predicted effect-site concentration and measured bispectral index is problematic during intravenous anesthesia with target-controlled infusion of propofol and remifentanil. We hypothesized that bispectral index dur...
VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.
IEEE transactions on biomedical circuits and systems
Feb 1, 2018
Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (...
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