AIMC Topic: Electroencephalography

Clear Filters Showing 2231 to 2240 of 2295 articles

The combined use of virtual reality and EEG to study language processing in naturalistic environments.

Behavior research methods
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
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
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
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
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 (...

As above, so below? Towards understanding inverse models in BCI.

Journal of neural engineering
OBJECTIVE: In brain-computer interfaces (BCI), measurements of the user's brain activity are classified into commands for the computer. With EEG-based BCIs, the origins of the classified phenomena are often considered to be spatially localized in the...

Inferring imagined speech using EEG signals: a new approach using Riemannian manifold features.

Journal of neural engineering
OBJECTIVE: In this paper, we investigate the suitability of imagined speech for brain-computer interface (BCI) applications.

Research: Use of Dry Electroencephalogram and Support Vector for Objective Pain Assessment.

Biomedical instrumentation & technology
The reliability of normal gel-based electrode electroencephalogram (EEG) for measuring pain has been validated. To date, however, few documented trials have used dry EEG for pain quantification. The primary goal of this study was to objectively quant...

Human emotion classification based on multiple physiological signals by wearable system.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Human emotion classification is traditionally achieved using multi-channel electroencephalogram (EEG) signal, which requires costly equipment and complex classification algorithms.

Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Epilepsy is a common chronic neurological disorder of the brain. Clinically, epileptic seizures are usually detected via the continuous monitoring of electroencephalogram (EEG) signals by experienced neurophysiologists.