AIMC Topic: Electroencephalography

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Machine learning classification of active viewing of pain and non-pain images using EEG does not exceed chance in external validation samples.

Cognitive, affective & behavioral neuroscience Feb 18, 2025
Previous research has demonstrated that machine learning (ML) could not effectively decode passive observation of neutral versus pain photographs by using electroencephalogram (EEG) data. Consequently, the present study explored whether active viewin...
Machine Learning Female Young Adult Adult Humans Facial Expression Evoked Potentials Facial Recognition Pain Perception Male Electroencephalography Pain
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Explaining electroencephalogram channel and subband sensitivity for alcoholism detection.

Computers in biology and medicine Feb 18, 2025
Alcoholism, a progressive loss of control over alcohol consumption, deteriorates mental and physical health over time. Automatic alcoholism detection can aid in early interventions and timely corrective actions. For this purpose, electroencephalogram...
Humans Neural Networks, Computer Adult Male Alcoholism Machine Learning Middle Aged Female Electroencephalography Signal Processing, Computer-Assisted
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A systematic literature review of machine learning techniques for the detection of attention-deficit/hyperactivity disorder using MRI and/or EEG data.

Neuroscience Feb 18, 2025
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition common in teenagers across the globe. Neuroimaging and Machine Learning (ML) advancements have revolutionized its diagnosis and treatment approaches. Although, the rese...
Attention Deficit Disorder with Hyperactivity Magnetic Resonance Imaging Electroencephalography Neuroimaging Humans Machine Learning Brain
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Supervised machine learning compared to large language models for identifying functional seizures from medical records.

Epilepsia Feb 17, 2025
OBJECTIVE: The Functional Seizures Likelihood Score (FSLS) is a supervised machine learning-based diagnostic score that was developed to differentiate functional seizures (FS) from epileptic seizures (ES). In contrast to this targeted approach, large...
Male Large Language Models Female ROC Curve Young Adult Humans Electroencephalography Machine Learning Adult Language Middle Aged Adolescent Seizures Supervised Machine Learning
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Bridging Neuroscience and Machine Learning: A Gender-Based Electroencephalogram Framework for Guilt Emotion Identification.

Sensors (Basel, Switzerland) Feb 17, 2025
This study explores the link between the emotion "guilt" and human EEG data, and investigates the influence of gender differences on the expression of guilt and neutral emotions in response to visual stimuli. Additionally, the stimuli used in the stu...
Brain Female Electroencephalography Young Adult Male Sex Factors Adult Support Vector Machine Humans Neurosciences Emotions Guilt Machine Learning
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A hybrid optimization-enhanced 1D-ResCNN framework for epileptic spike detection in scalp EEG signals.

Scientific reports Feb 17, 2025
In order to detect epileptic spikes, this paper suggests a deep learning architecture that blends 1D residual convolutional neural networks (1D-ResCNN) with a hybrid optimization strategy. The Layer-wise Adaptive Moments (LAMB) and AdamW algorithms h...
Scalp Female Epilepsy Adult Humans Deep Learning Male Signal Processing, Computer-Assisted Neural Networks, Computer Electroencephalography Algorithms
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Efficient Neural Network Classification of Parkinson's Disease and Schizophrenia Using Resting-State EEG Data.

Brain topography Feb 17, 2025
Timely identification of Parkinson's disease and schizophrenia is crucial for the effective management and enhancement of patients' quality of life. The utilization of electroencephalogram (EEG) monitoring applications has proven instrumental in diag...
Male Middle Aged Parkinson Disease Electroencephalography Schizophrenia Brain Female Aged Humans Neural Networks, Computer
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Latent alignment in deep learning models for EEG decoding.

Journal of neural engineering Feb 17, 2025
. Brain-computer interfaces (BCIs) face a significant challenge due to variability in electroencephalography (EEG) signals across individuals. While recent approaches have focused on standardizing input signal distributions, we propose that aligning ...
Electroencephalography Brain-Computer Interfaces Event-Related Potentials, P300 Sleep Stages Adult Male Deep Learning Imagination Humans Female
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Enhancing detection of SSVEPs using discriminant compacted network.

Journal of neural engineering Feb 14, 2025
. Steady-state visual evoked potential-based brain-computer interfaces (SSVEP-BCIs) have gained significant attention due to their simplicity, high signal to noise ratio and high information transfer rates (ITRs). Currently, accurate detection is a c...
Female Adult Male Deep Learning Humans Neural Networks, Computer Evoked Potentials, Visual Photic Stimulation Discriminant Analysis Electroencephalography Brain-Computer Interfaces
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Depth-sensor-based shared control assistance for mobility and object manipulation: toward long-term home-use of BCI-controlled assistive robotic devices.

Journal of neural engineering Feb 14, 2025
Assistive robots can be developed to restore or provide more autonomy for individuals with motor impairments. In particular, power wheelchairs can compensate lower-limb impairments, while robotic manipulators can compensate upper-limbs impairments. R...
Self-Help Devices Quadriplegia Adult Humans Female Brain-Computer Interfaces Male Electroencephalography Wheelchairs Robotics Equipment Design
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