AIMC Topic: Electroencephalography

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Efficient in Vivo Neural Signal Compression Using an Autoencoder-Based Neural Network.

IEEE transactions on biomedical circuits and systems May 28, 2024
Conventional in vivo neural signal processing involves extracting spiking activity within the recorded signals from an ensemble of neurons and transmitting only spike counts over an adequate interval. However, for brain-computer interface (BCI) appli...
Brain-Computer Interfaces Data Compression Neural Networks, Computer Algorithms Electroencephalography Animals Signal Processing, Computer-Assisted Neurons
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PyHFO: lightweight deep learning-powered end-to-end high-frequency oscillations analysis application.

Journal of neural engineering May 28, 2024
. This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning (DL) methodologies in detecting neurophysiological biomarkers for epileptogenic zones from EEG recordings.. We introdu...
Software Algorithms Animals Humans Electroencephalography Epilepsy Deep Learning Hippocampus Rats
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EEG Emotion Recognition Network Based on Attention and Spatiotemporal Convolution.

Sensors (Basel, Switzerland) May 27, 2024
Human emotions are complex psychological and physiological responses to external stimuli. Correctly identifying and providing feedback on emotions is an important goal in human-computer interaction research. Compared to facial expressions, speech, or...
Electroencephalography Signal Processing, Computer-Assisted Attention Algorithms Humans Brain Neural Networks, Computer Emotions
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An automated approach for predicting HAMD-17 scores via divergent selective focused multi-heads self-attention network.

Brain research bulletin May 26, 2024
This study introduces the Divergent Selective Focused Multi-heads Self-Attention Network (DSFMANet), an innovative deep learning model devised to automatically predict Hamilton Depression Rating Scale-17 (HAMD-17) scores in patients with depression. ...
Adult Male Deep Learning Psychiatric Status Rating Scales Depression Electroencephalography Humans Female Attention
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Detection Method of Epileptic Seizures Using a Neural Network Model Based on Multimodal Dual-Stream Networks.

Sensors (Basel, Switzerland) May 24, 2024
Epilepsy is a common neurological disorder, and its diagnosis mainly relies on the analysis of electroencephalogram (EEG) signals. However, the raw EEG signals contain limited recognizable features, and in order to increase the recognizable features ...
Signal Processing, Computer-Assisted Electroencephalography Epilepsy Seizures Humans Neural Networks, Computer Algorithms
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Epileptic Seizure Prediction Using Spatiotemporal Feature Fusion on EEG.

International journal of neural systems May 22, 2024
Electroencephalography (EEG) plays a crucial role in epilepsy analysis, and epileptic seizure prediction has significant value for clinical treatment of epilepsy. Currently, prediction methods using Convolutional Neural Network (CNN) primarily focus ...
Seizures Signal Processing, Computer-Assisted Electroencephalography Epilepsy Humans Neural Networks, Computer Sensitivity and Specificity
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Evaluation of EEG Signals by Spectral Peak Methods and Statistical Correlation for Mental State Discrimination Induced by Arithmetic Tasks.

Sensors (Basel, Switzerland) May 22, 2024
Bringing out brain activity through the interpretation of EEG signals is a challenging problem that involves combined methods of signal analysis. The issue of classifying mental states induced by arithmetic tasks can be solved through various classif...
Humans Neural Networks, Computer Adult Signal Processing, Computer-Assisted Male Support Vector Machine Algorithms Discriminant Analysis Brain Electroencephalography Female
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Deep learning-based auditory attention decoding in listeners with hearing impairment.

Journal of neural engineering May 22, 2024
This study develops a deep learning (DL) method for fast auditory attention decoding (AAD) using electroencephalography (EEG) from listeners with hearing impairment (HI). It addresses three classification tasks: differentiating noise from speech-in-n...
Attention Hearing Aids Hearing Loss Deep Learning Noise Electroencephalography Speech Perception Auditory Perception Neural Networks, Computer Female Aged Adult Male Middle Aged Humans
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A novel feature extraction method PSS-CSP for binary motor imagery - based brain-computer interfaces.

Computers in biology and medicine May 20, 2024
In order to improve the performance of binary motor imagery (MI) - based brain-computer interfaces (BCIs) using electroencephalography (EEG), a novel method (PSS-CSP) is proposed, which combines spectral subtraction with common spatial pattern. Spect...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Brain Imagination Support Vector Machine Humans Electroencephalography Algorithms
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Formulation of Common Spatial Patterns for Multi-Task Hyperscanning BCI.

IEEE transactions on bio-medical engineering May 20, 2024
This work proposes a new formulation for common spatial patterns (CSP), often used as a powerful feature extraction technique in brain-computer interfacing (BCI) and other neurological studies. In this approach, applied to multiple subjects' data and...
Algorithms Brain Female Humans Electroencephalography Signal Processing, Computer-Assisted Adult Brain-Computer Interfaces Male Support Vector Machine
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