AIMC Topic: Electroencephalography

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EEG-Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review.

Computational intelligence and neuroscience Jun 17, 2022
Epileptic seizure is one of the most chronic neurological diseases that instantaneously disrupts the lifestyle of affected individuals. Toward developing novel and efficient technology for epileptic seizure management, recent diagnostic approaches ha...
Deep Learning Support Vector Machine Seizures Humans Signal Processing, Computer-Assisted Electroencephalography Algorithms Epilepsy
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A novel deep learning model based on the ICA and Riemannian manifold for EEG-based emotion recognition.

Journal of neuroscience methods Jun 8, 2022
BACKGROUND: The EEG-based emotion recognition is one of the primary research orientations in the field of emotional intelligence and human-computer interaction (HCI).
Humans Deep Learning Emotions Electroencephalography Neural Networks, Computer Algorithms
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The Masking Impact of Intra-Artifacts in EEG on Deep Learning-Based Sleep Staging Systems: A Comparative Study.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 2, 2022
Elimination of intra-artifacts in EEG has been overlooked in most of the existing sleep staging systems, especially in deep learning-based approaches. Whether intra-artifacts, originated from the eye movement, chin muscle firing, or heart beating, et...
Deep Learning China Sleep Electroencephalography Artifacts Humans Signal Processing, Computer-Assisted Algorithms
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Symmetric Convolutional and Adversarial Neural Network Enables Improved Mental Stress Classification From EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society May 30, 2022
Electroencephalography (EEG) is widely used for mental stress classification, but effective feature extraction and transfer across subjects remain challenging due to its variability. In this paper, a novel deep neural network combining convolutional ...
Humans Neural Networks, Computer Electroencephalography Attention
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Decoding neural activity preceding balance loss during standing with a lower-limb exoskeleton using an interpretable deep learning model.

Journal of neural engineering May 26, 2022
Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb function in these populations have seen an increase in the use of wearable robotic systems; however, fall prevention measures in these systems require ear...
Humans Adult Exoskeleton Device Electromyography Brain-Computer Interfaces Deep Learning Electroencephalography
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A Data-Driven Adaptive Emotion Recognition Model for College Students Using an Improved Multifeature Deep Neural Network Technology.

Computational intelligence and neuroscience May 26, 2022
With the increasing pressure on college students in terms of study, work, emotion, and life, the emotional changes of college students are becoming more and more obvious. For college student management workers, if they can accurately grasp the emotio...
Technology Students Humans Neural Networks, Computer Emotions Electroencephalography
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Primary Experiences with Robot-assisted Navigation-based Frameless Stereo-electroencephalography: Higher Accuracy than Neuronavigation-guided Manual Adjustment.

Neurologia medico-chirurgica May 25, 2022
The use of robot-assisted frameless stereotactic electroencephalography (SEEG) is becoming more common. Among available robotic arms, Stealth Autoguide (SA) (Medtronic, Minneapolis, MN, USA) functions as an optional instrument of the neuronavigation ...
Electrodes, Implanted Neuronavigation Electroencephalography Stereotaxic Techniques Retrospective Studies Robotics Humans
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Short report: surgery for implantable brain-computer interface assisted by robotic navigation system.

Acta neurochirurgica May 23, 2022
We present an implantable brain-computer interface surgical case assisted by robotic navigation system in an elderly patient with tetraplegia caused by cervical spinal cord injury. Left primary motor cortex was selected for implantation of microelect...
Robotic Surgical Procedures Brain-Computer Interfaces Robotics Electroencephalography Movement Quadriplegia Humans Aged
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A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram.

International journal of environmental research and public health May 23, 2022
The classification of sleep stages is an important process. However, this process is time-consuming, subjective, and error-prone. Many automated classification methods use electroencephalogram (EEG) signals for classification. These methods do not cl...
Electroencephalography Sleep Sleep Stages Neural Networks, Computer Deep Learning
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A Bimodal Deep Learning Architecture for EEG-fNIRS Decoding of Overt and Imagined Speech.

IEEE transactions on bio-medical engineering May 19, 2022
OBJECTIVE: Brain-computer interfaces (BCI) studies are increasingly leveraging different attributes of multiple signal modalities simultaneously. Bimodal data acquisition protocols combining the temporal resolution of electroencephalography (EEG) wit...
Brain-Computer Interfaces Speech Electroencephalography Humans Neural Networks, Computer Deep Learning
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