AIMC Topic: Electroencephalography
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A Systematic Review of Virtual Reality and Robot Therapy as Recent Rehabilitation Technologies Using EEG-Brain-Computer Interface Based on Movement-Related Cortical Potentials.
Biosensors
Dec 6, 2022
To enhance the treatment of motor function impairment, patients' brain signals for self-control as an external tool may be an extraordinarily hopeful option. For the past 10 years, researchers and clinicians in the brain-computer interface (BCI) fiel...
A comparison between robot-guided and stereotactic frame-based stereoelectroencephalography (SEEG) electrode implantation for drug-resistant epilepsy.
Journal of robotic surgery
Dec 1, 2022
The original stereoelectroencephalography frame-based implantation technique has been proven to be safe and effective. But this procedure is complicated and time-consuming. With the development of modern robotic technology, robot-guided intracerebral...
Automatic seizure detection by convolutional neural networks with computational complexity analysis.
Computer methods and programs in biomedicine
Nov 25, 2022
BACKGROUND AND OBJECTIVES: Nowadays, an automated computer-aided diagnosis (CAD) is an approach that plays an important role in the detection of health issues. The main advantages should be in early diagnosis, including high accuracy and low computat...
Sleep Staging Framework with Physiologically Harmonized Sub-Networks.
Methods (San Diego, Calif.)
Nov 24, 2022
Sleep screening is an important tool for both healthcare and neuroscientific research. Automatic sleep scoring is an alternative to the time-consuming gold-standard manual scoring procedure. Recently there have seen promising results on automatic sta...
Real-time noise cancellation with deep learning.
PloS one
Nov 21, 2022
Biological measurements are often contaminated with large amounts of non-stationary noise which require effective noise reduction techniques. We present a new real-time deep learning algorithm which produces adaptively a signal opposing the noise so ...
NeuroGrasp: Real-Time EEG Classification of High-Level Motor Imagery Tasks Using a Dual-Stage Deep Learning Framework.
IEEE transactions on cybernetics
Nov 18, 2022
Brain-computer interfaces (BCIs) have been widely employed to identify and estimate a user's intention to trigger a robotic device by decoding motor imagery (MI) from an electroencephalogram (EEG). However, developing a BCI system driven by MI relate...
Detection of K-complexes in EEG waveform images using faster R-CNN and deep transfer learning.
BMC medical informatics and decision making
Nov 17, 2022
BACKGROUND: The electroencephalography (EEG) signal carries important information about the electrical activity of the brain, which may reveal many pathologies. This information is carried in certain waveforms and events, one of which is the K-comple...
Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task.
Computers in biology and medicine
Nov 15, 2022
Virtual reality surgical simulators have facilitated surgical education by providing a safe training environment. Electroencephalography (EEG) has been employed to assess neuroelectric activity during surgical performance. Machine learning (ML) has b...
Novel 3D video action recognition deep learning approach for near real time epileptic seizure classification.
Scientific reports
Nov 15, 2022
Seizure semiology is a well-established method to classify epileptic seizure types, but requires a significant amount of resources as long-term Video-EEG monitoring needs to be visually analyzed. Therefore, computer vision based diagnosis support too...
Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy.
IEEE journal of biomedical and health informatics
Nov 10, 2022
The present study investigates the effectiveness of a deep learning neural network for non-invasively localizing the seizure onset zone (SOZ) using multi-modal MRI data that are clinically acquired from children with drug-resistant epilepsy. A cortic...
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