AIMC Topic: Electroencephalography

Clear Filters Showing 1731 to 1740 of 2295 articles

A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems.

Methods (San Diego, Calif.)
EEG is a standard non-invasive technique used in neural disease diagnostics and neurosciences. Frequency-tagging is an increasingly popular experimental paradigm that efficiently tests brain function by measuring EEG responses to periodic stimulation...

Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing.

Scientific reports
Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growin...

Automated analysis of brain activity for seizure detection in zebrafish models of epilepsy.

Journal of neuroscience methods
BACKGROUND: Epilepsy is a chronic neurological condition, with over 30% of cases unresponsive to treatment. Zebrafish larvae show great potential to serve as an animal model of epilepsy in drug discovery. Thanks to their high fecundity and relatively...

Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System.

BioMed research international
A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, "teeth clenching" state detector, and a steady-state visual evoked...

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PloS one
Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm ...

A new near-lossless EEG compression method using ANN-based reconstruction technique.

Computers in biology and medicine
Compression algorithm is an essential part of Telemedicine systems, to store and transmit large amount of medical signals. Most of existing compression methods utilize fixed transforms such as discrete cosine transform (DCT) and wavelet and usually c...

Auditory prediction errors as individual biomarkers of schizophrenia.

NeuroImage. Clinical
Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence collected through patient interview. We aim to develop an objective biologically-based computational tool which aids diagnosis and relies on accessible ...

Towards Improved Design and Evaluation of Epileptic Seizure Predictors.

IEEE transactions on bio-medical engineering
OBJECTIVE: Key issues in the epilepsy seizure prediction research are (1) the reproducibility of results (2) the inability to compare multiple approaches directly. To overcome these problems, the seizure prediction challenge was organized on Kaggle.c...

EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN.

BioMed research international
Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new c...

Learning from label proportions in brain-computer interfaces: Online unsupervised learning with guarantees.

PloS one
OBJECTIVE: Using traditional approaches, a brain-computer interface (BCI) requires the collection of calibration data for new subjects prior to online use. Calibration time can be reduced or eliminated e.g., by subject-to-subject transfer of a pre-tr...