AIMC Topic: Electroencephalography
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Time-Frequency Representation and Convolutional Neural Network-Based Emotion Recognition.
IEEE transactions on neural networks and learning systems
Jul 6, 2021
Emotions composed of cognizant logical reactions toward various situations. Such mental responses stem from physiological, cognitive, and behavioral changes. Electroencephalogram (EEG) signals provide a noninvasive and nonradioactive solution for emo...
A Hybrid Brain-Computer Interface for Real-Life Meal-Assist Robot Control.
Sensors (Basel, Switzerland)
Jul 4, 2021
Assistant devices such as meal-assist robots aid individuals with disabilities and support the elderly in performing daily activities. However, existing meal-assist robots are inconvenient to operate due to non-intuitive user interfaces, requiring ad...
Artificial Intelligence Analysis of EEG Amplitude in Intensive Heart Care.
Journal of healthcare engineering
Jul 2, 2021
This article first studied the morphological characteristics of the EEG for intensive cardiac care; that is, based on the analysis of the mechanism of disease diagnosis and treatment, a signal processing and machine learning model was constructed. Th...
A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG.
PloS one
Jun 25, 2021
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments in social interaction, speech and nonverbal communication, and restricted or repetitive behaviors. Currently Electroencephalography (EEG) is the most...
Universum based Lagrangian twin bounded support vector machine to classify EEG signals.
Computer methods and programs in biomedicine
Jun 24, 2021
BACKGROUND AND OBJECTIVE: The detection of brain-related problems and neurological disorders like epilepsy, sleep disorder, and so on is done by using electroencephalogram (EEG) signals which contain noisy signals and outliers. Universum data contain...
Epileptic Seizure Detection on an Ultra-Low-Power Embedded RISC-V Processor Using a Convolutional Neural Network.
Biosensors
Jun 23, 2021
The treatment of refractory epilepsy via closed-loop implantable devices that act on seizures either by drug release or electrostimulation is a highly attractive option. For such implantable medical devices, efficient and low energy consumption, smal...
MEG Source Localization via Deep Learning.
Sensors (Basel, Switzerland)
Jun 22, 2021
We present a deep learning solution to the problem of localization of magnetoencephalography (MEG) brain signals. The proposed deep model architectures are tuned to single and multiple time point MEG data, and can estimate varying numbers of dipole s...
Exploring the Use of Brain-Computer Interfaces in Stroke Neurorehabilitation.
BioMed research international
Jun 18, 2021
With the continuous development of artificial intelligence technology, "brain-computer interfaces" are gradually entering the field of medical rehabilitation. As a result, brain-computer interfaces (BCIs) have been included in many countries' strateg...
Deep learning of resting-state electroencephalogram signals for three-class classification of Alzheimer's disease, mild cognitive impairment and healthy ageing.
Journal of neural engineering
Jun 17, 2021
This study aimed to produce a novel deep learning (DL) model for the classification of subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI) subjects and healthy ageing (HA) subjects using resting-state scalp electroencephalogram (E...
Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM.
Biosensors
Jun 16, 2021
To assist patients with restricted mobility to control wheelchair freely, this paper presents an eye-movement-controlled wheelchair prototype based on a flexible hydrogel biosensor and Wavelet Transform-Support Vector Machine (WT-SVM) algorithm. Cons...
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