AIMC Topic: Electroencephalography

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Classification of mental workload using brain connectivity and machine learning on electroencephalogram data.

Scientific reports Apr 21, 2024
Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In this paper, we propose innovative methods to assess...
Humans Adult Support Vector Machine Brain Machine Learning Electroencephalography Male Workload Female Cognition Algorithms Young Adult
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A single-joint multi-task motor imagery EEG signal recognition method based on Empirical Wavelet and Multi-Kernel Extreme Learning Machine.

Journal of neuroscience methods Apr 19, 2024
BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals f...
Female Imagination Humans Young Adult Machine Learning Adult Brain-Computer Interfaces Electroencephalography Brain Male Wavelet Analysis Signal Processing, Computer-Assisted Motor Activity Wrist
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Automatic Detection of Scalp High-Frequency Oscillations Based on Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 19, 2024
Scalp high-frequency oscillations (sHFOs) are a promising non-invasive biomarker of epilepsy. However, the visual marking of sHFOs is a time-consuming and subjective process, existing automatic detectors based on single-dimensional analysis have diff...
Humans Reproducibility of Results Deep Learning Electroencephalography Epilepsy Scalp
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Imagined speech classification exploiting EEG power spectrum features.

Medical & biological engineering & computing Apr 18, 2024
Imagined speech recognition has developed as a significant topic of research in the field of brain-computer interfaces. This innovative technique has great promise as a communication tool, providing essential help to those with impairments. An imagin...
Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted Adult Male Speech Humans Brain-Computer Interfaces Imagination Female Young Adult Algorithms Brain
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Artificial intelligence/machine learning for epilepsy and seizure diagnosis.

Epilepsy & behavior : E&B Apr 17, 2024
Accurate seizure and epilepsy diagnosis remains a challenging task due to the complexity and variability of manifestations, which can lead to delayed or missed diagnosis. Machine learning (ML) and artificial intelligence (AI) is a rapidly developing ...
Electroencephalography Epilepsy Seizures Humans Artificial Intelligence Machine Learning
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Attention-based deep convolutional neural network for classification of generalized and focal epileptic seizures.

Epilepsy & behavior : E&B Apr 17, 2024
Epilepsy affects over 50 million people globally. Electroencephalography is critical for epilepsy diagnosis, but manual seizure classification is time-consuming and requires extensive expertise. This paper presents an automated multi-class seizure cl...
Deep Learning Electroencephalography Seizures Young Adult Adult Male Attention Epilepsies, Partial Epilepsy, Generalized Humans Neural Networks, Computer Female
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Convolutional spiking neural networks for intent detection based on anticipatory brain potentials using electroencephalogram.

Scientific reports Apr 17, 2024
Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition o...
Humans Neural Networks, Computer Brain Electroencephalography Intention
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A GRU-CNN model for auditory attention detection using microstate and recurrence quantification analysis.

Scientific reports Apr 17, 2024
Attention as a cognition ability plays a crucial role in perception which helps humans to concentrate on specific objects of the environment while discarding others. In this paper, auditory attention detection (AAD) is investigated using different dy...
Electroencephalography Machine Learning Attention Brain Humans Brain Mapping Neural Networks, Computer
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MSLTE: multiple self-supervised learning tasks for enhancing EEG emotion recognition.

Journal of neural engineering Apr 17, 2024
. The instability of the EEG acquisition devices may lead to information loss in the channels or frequency bands of the collected EEG. This phenomenon may be ignored in available models, which leads to the overfitting and low generalization of the mo...
Emotions Electroencephalography Supervised Machine Learning Datasets as Topic Humans
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Differentiating ischemic stroke patients from healthy subjects using a large-scale, retrospective EEG database and machine learning methods.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Apr 16, 2024
OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presenting with ischemic stroke from a healthy cohort of subjects. The model relies on a 3-min resting electroencephalogram (EEG) recording from which featu...
Humans Electroencephalography Machine Learning Signal Processing, Computer-Assisted Databases, Factual Middle Aged Brain Waves Aged, 80 and over Brain Predictive Value of Tests Case-Control Studies Female Retrospective Studies Adult Ischemic Stroke Diagnosis, Computer-Assisted Reproducibility of Results Time Factors Male Aged Diagnosis, Differential
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