AIMC Topic: Electroencephalography

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Data-driven electrophysiological feature based on deep learning to detect epileptic seizures.

Journal of neural engineering Sep 30, 2021
. To identify a new electrophysiological feature characterising the epileptic seizures, which is commonly observed in different types of epilepsy.. We recorded the intracranial electroencephalogram (iEEG) of 21 patients (12 women and 9 men) with mult...
Male Support Vector Machine Electroencephalography Deep Learning Epilepsy Seizures Humans Female
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Recognition of EEG Signals from Imagined Vowels Using Deep Learning Methods.

Sensors (Basel, Switzerland) Sep 29, 2021
The use of imagined speech with electroencephalographic (EEG) signals is a promising field of brain-computer interfaces (BCI) that seeks communication between areas of the cerebral cortex related to language and devices or machines. However, the comp...
Speech Humans Algorithms Brain-Computer Interfaces Electroencephalography Deep Learning
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Effect of combining features generated through non-linear analysis and wavelet transform of EEG signals for the diagnosis of encephalopathy.

Neuroscience letters Sep 25, 2021
Electroencephalogram (EEG) signals portray hidden neuronal interactions in the brain and indicate brain dynamics. These signals are dynamic, complex, chaotic and nonlinear, the nature of which is represented with features - fractal dimensions, entrop...
Support Vector Machine Wavelet Analysis Electroencephalography Nonlinear Dynamics Humans Brain Diseases
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ECG-based machine-learning algorithms for heartbeat classification.

Scientific reports Sep 21, 2021
Electrocardiogram (ECG) signals represent the electrical activity of the human hearts and consist of several waveforms (P, QRS, and T). The duration and shape of each waveform and the distances between different peaks are used to diagnose heart disea...
Electrocardiography Machine Learning Humans Heart Rate Electroencephalography Neural Networks, Computer Algorithms
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Optimizing Motor Intention Detection With Deep Learning: Towards Management of Intraoperative Awareness.

IEEE transactions on bio-medical engineering Sep 20, 2021
OBJECTIVE: This article shows the interest in deep learning techniques to detect motor imagery (MI) from raw electroencephalographic (EEG) signals when a functional electrical stimulation is added or not. Impacts of electrode montages and bandwidth a...
Deep Learning Imagination Electroencephalography Intraoperative Awareness Humans Algorithms Intention Brain-Computer Interfaces
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EEG Mental Stress Assessment Using Hybrid Multi-Domain Feature Sets of Functional Connectivity Network and Time-Frequency Features.

Sensors (Basel, Switzerland) Sep 20, 2021
Exposure to mental stress for long period leads to serious accidents and health problems. To avoid negative consequences on health and safety, it is very important to detect mental stress at its early stages, i.e., when it is still limited to acute o...
Machine Learning Stress, Psychological Support Vector Machine Electroencephalography Humans
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EEG-Based Personality Prediction Using Fast Fourier Transform and DeepLSTM Model.

Computational intelligence and neuroscience Sep 20, 2021
In this paper, a deep long short term memory (DeepLSTM) network to classify personality traits using the electroencephalogram (EEG) signals is implemented. For this research, the Myers-Briggs Type Indicator (MBTI) model for predicting personality is ...
Personality Electroencephalography Fourier Analysis Neural Networks, Computer Algorithms Humans
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The emergence of machine learning in auditory neural impairment: A systematic review.

Neuroscience letters Sep 15, 2021
Hearing loss is a common neurodegenerative disease that can start at any stage of life. Misalignment of the auditory neural impairment may impose challenges in processing incoming auditory stimulus that can be measured using electroencephalography (E...
Evoked Potentials, Auditory Hearing Loss Electroencephalography Signal Processing, Computer-Assisted Brain Support Vector Machine Humans
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Neurosurgical robot-assistant stereoelectroencephalography system: Operability and accuracy.

Brain and behavior Sep 14, 2021
BACKGROUND: Fine operation has been an eternal topic in neurosurgery. There were many problems in functional neurosurgery field with high precision requirements. Our study aims to explore the operability, accuracy and postoperative effect of robot-as...
Stereotaxic Techniques Drug Resistant Epilepsy Robotics Electroencephalography Humans Retrospective Studies
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Speed controller-based fuzzy logic for a biosignal-feedbacked cycloergometer.

Computer methods in biomechanics and biomedical engineering Sep 11, 2021
Nowadays, fuzzy-logic systems are implemented to control machinery or processes that previously required human manipulation. The main objective of this research is to propose a controller based on fuzzy-logic that uses bio-signals for decision making...
Electroencephalography Electromyography Humans Fuzzy Logic
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