AIMC Topic: Electroencephalography
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Hybrid fuzzy deep neural network toward temporal-spatial-frequency features learning of motor imagery signals.
Scientific reports
Dec 25, 2022
Achieving an efficient and reliable method is essential to interpret a user's brain wave and deliver an accurate response in biomedical signal processing. However, EEG patterns exhibit high variability across time and uncertainty due to noise and it ...
A Method of Intraoperative Registration Verification to Prevent Accuracy Errors in Robot-Assisted Stereotactic Electroencephalography Electrode Placement.
World neurosurgery
Dec 20, 2022
BACKGROUND: Robotic-assisted stereotactic electroencephalography (sEEG) electrode placement is increasingly common at specialized epilepsy centers. High accuracy and low complication rates are essential to realizing the benefits of sEEG surgery. The ...
The accuracy of a novel self-tapping bone fiducial marker for frameless robot-assisted stereo-electro-encephalography implantation and registration techniques.
The international journal of medical robotics + computer assisted surgery : MRCAS
Dec 17, 2022
BACKGROUND: We aimed to evaluate the accuracy and safety of a novel self-tapping bone fiducial as a registration technique for stereoelectroencephalography (SEEG) implantation.
Fast Sleep Stage Classification Using Cascaded Support Vector Machines with Single-Channel EEG Signals.
Sensors (Basel, Switzerland)
Dec 16, 2022
Long-term sleep stage monitoring is very important for the diagnosis and treatment of insomnia. With the development of wearable electroencephalogram (EEG) devices, we developed a fast and accurate sleep stage classification method in this study with...
Computer-aided diagnosis of autism spectrum disorder from EEG signals using deep learning with FAWT and multiscale permutation entropy features.
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Dec 14, 2022
Autism spectrum disorder (ASD), a neurodevelopment disorder, is characterized by significant difficulties in social interaction and emerges as a major threat to children. Its computer-aided diagnosis used by neurologists improves the detection proces...
An Efficient AP-ANN-Based Multimethod Fusion Model to Detect Stress through EEG Signal Analysis.
Computational intelligence and neuroscience
Dec 12, 2022
Stress is a universal emotion that every human experiences daily. Psychologists say stress may lead to heart attack, depression, hypertension, strokes, or even sudden death. Many technical explorations like stress detection through facial expression,...
Teleoperation control of a wheeled mobile robot based on Brain-machine Interface.
Mathematical biosciences and engineering : MBE
Dec 9, 2022
This paper presents a novel teleoperation system using Electroencephalogram (EEG) to control the motion of a wheeled mobile robot (WMR). Different from the other traditional motion controlling method, the WMR is braked with the EEG classification res...
Brain-Controlled 2D Navigation Robot Based on a Spatial Gradient Controller and Predictive Environmental Coordinator.
IEEE journal of biomedical and health informatics
Dec 8, 2022
OBJECTIVE: Brain-computer interfaces (BCIs) have been used in two-dimensional (2D) navigation robotic devices, such as brain-controlled wheelchairs and brain-controlled vehicles. However, contemporary BCI systems are driven by binary selective contro...
Characterizing physiological high-frequency oscillations using deep learning.
Journal of neural engineering
Dec 7, 2022
Intracranially-recorded interictal high-frequency oscillations (HFOs) have been proposed as a promising spatial biomarker of the epileptogenic zone. However, HFOs can also be recorded in the healthy brain regions, which complicates the interpretation...
A Transferable Deep Learning Prognosis Model for Predicting Stroke Patients' Recovery in Different Rehabilitation Trainings.
IEEE journal of biomedical and health informatics
Dec 7, 2022
Since the underlying mechanisms of neurorehabilitation are not fully understood, the prognosis of stroke recovery faces significant difficulties. Recovery outcomes can vary when undergoing different treatments; however, few models have been developed...
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