AIMC Topic: Electroencephalography

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A deep learning method for single-trial EEG classification in RSVP task based on spatiotemporal features of ERPs.

Journal of neural engineering Aug 13, 2021
. Single-trial electroencephalography (EEG) classification is of great importance in the rapid serial visual presentation (RSVP) task. Convolutional neural networks (CNNs), as one of the mainstream deep learning methods, have been proven to be effect...
Electroencephalography Evoked Potentials Neural Networks, Computer Deep Learning
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Linear and non-linear feature extraction from rat electrocorticograms for seizure detection by support vector machine.

Biomedizinische Technik. Biomedical engineering Aug 12, 2021
Seizures, the main symptom of epilepsy, are provoked due to a neurological disorder that underlies the disease. The accurate detection of seizures is a crucial step in any procedure of treatment. In the present study, electrocorticogram (ECoG) signal...
Seizures Signal Processing, Computer-Assisted Electroencephalography Epilepsy Rats Support Vector Machine Algorithms Animals
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A Hybrid-Domain Deep Learning-Based BCI For Discriminating Hand Motion Planning From EEG Sources.

International journal of neural systems Aug 11, 2021
In this paper, a hybrid-domain deep learning (DL)-based neural system is proposed to decode hand movement preparation phases from electroencephalographic (EEG) recordings. The system exploits information extracted from the temporal-domain and time-fr...
Brain-Computer Interfaces Deep Learning Electroencephalography Machine Learning Algorithms Neural Networks, Computer
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EEG Channel Correlation Based Model for Emotion Recognition.

Computers in biology and medicine Aug 10, 2021
Emotion recognition using Artificial Intelligence (AI) is a fundamental prerequisite to improve Human-Computer Interaction (HCI). Recognizing emotion from Electroencephalogram (EEG) has been globally accepted in many applications such as intelligent ...
Emotions Electroencephalography Arousal Humans Neural Networks, Computer Artificial Intelligence
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Machine Learning for personalised stress detection: Inter-individual variability of EEG-ECG markers for acute-stress response.

Computer methods and programs in biomedicine Aug 8, 2021
Stress appears as a response for a broad variety of physiological stimuli. It does vary among individuals in amplitude, phase and frequency. Thus, the necessity for personalised diagnosis is key to prevent stress-related diseases. In order to evaluat...
Machine Learning Young Adult Adolescent Electrocardiography Adult Humans Electroencephalography Exercise Test
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Detection of EEG burst-suppression in neurocritical care patients using an unsupervised machine learning algorithm.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Aug 5, 2021
OBJECTIVE: The burst suppression pattern in clinical electroencephalographic (EEG) recordings is an important diagnostic tool because of its association with comas of various etiologies, as with hypoxia, drug related intoxication or deep anesthesia. ...
Nervous System Diseases Electroencephalography Critical Care Humans Algorithms Male Middle Aged Unsupervised Machine Learning Intensive Care Units Female
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Video-Based Detection of Generalized Tonic-Clonic Seizures Using Deep Learning.

IEEE journal of biomedical and health informatics Aug 5, 2021
Timely detection of seizures is crucial to implement optimal interventions, and may help reduce the risk of sudden unexpected death in epilepsy (SUDEP) in patients with generalized tonic-clonic seizures (GTCSs). While video-based automated seizure de...
Humans Deep Learning Electroencephalography Seizures Neural Networks, Computer Retrospective Studies
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Utilizing deep neural networks and electroencephalogram for objective evaluation of surgeon's distraction during robot-assisted surgery.

Brain research Aug 2, 2021
OBJECTIVE: To develop an algorithm for objective evaluation of distraction of surgeons during robot-assisted surgery (RAS).
Humans Neural Networks, Computer Reproducibility of Results Adult Students, Medical Algorithms Female Models, Statistical Electroencephalography Psychomotor Performance General Surgery Robotic Surgical Procedures Middle Aged Deep Learning Clinical Competence Male Surgeons
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A deep learning based ensemble learning method for epileptic seizure prediction.

Computers in biology and medicine Jul 31, 2021
In epilepsy, patients suffer from seizures which cannot be controlled with medicines or surgical treatments in more than 30% of the cases. Prediction of epileptic seizures is extremely important so that they can be controlled with medication before t...
Seizures Electroencephalography Epilepsy Machine Learning Deep Learning Humans
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Affective Computing on Machine Learning-Based Emotion Recognition Using a Self-Made EEG Device.

Sensors (Basel, Switzerland) Jul 29, 2021
In this research, we develop an affective computing method based on machine learning for emotion recognition using a wireless protocol and a wearable electroencephalography (EEG) custom-designed device. The system collects EEG signals using an eight-...
Emotions Electroencephalography Machine Learning Support Vector Machine Humans Neural Networks, Computer
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