AIMC Topic: Electroencephalography
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Contrastive representation learning with transformers for robust auditory EEG decoding.
Scientific reports
Aug 6, 2025
Decoding of continuous speech from electroencephalography (EEG) presents a promising avenue for understanding neural mechanisms of auditory processing and developing applications in hearing diagnostics. Recent advances in deep learning have improved ...
PyNoetic: A modular python framework for no-code development of EEG brain-computer interfaces.
PloS one
Aug 6, 2025
Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) have emerged as a transformative technology with applications spanning robotics, virtual reality, medicine, and rehabilitation. However, existing BCI frameworks face several limitati...
VR-based gamma sensory stimulation: a pilot feasibility study.
Scientific reports
Aug 5, 2025
Alzheimer's disease (AD) presents a critical global health challenge, with current therapies offering limited efficacy and safety in halting disease progression. Gamma sensory stimulation (GSS) has emerged as a promising non-invasive neuromodulation ...
Cross-subject EEG signals-based emotion recognition using contrastive learning.
Scientific reports
Aug 3, 2025
Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant field in the domain of affective computing where EEG signals are the cause of reliable and objective applications. Despite these advancements, signific...
Classification accuracy of pain intensity induced by leg blood flow restriction during walking using machine learning based on electroencephalography.
Scientific reports
Jul 31, 2025
Pain assessment in clinical practice largely relies on patient-reported subjectivity. Although previous studies using fMRI and EEG have attempted objective pain evaluation, their focus has been limited to resting conditions. This study aimed to class...
EEG-based speech imagery decoding by dynamic hypergraph learning within projected and selected feature subspaces.
Journal of neural engineering
Jul 28, 2025
Speech imagery is a nascent paradigm that is receiving widespread attention in current brain-computer interface (BCI) research. By collecting the electroencephalogram (EEG) data generated when imagining the pronunciation of a sentence or word in huma...
Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device.
Scientific reports
Jul 20, 2025
Mild cognitive impairment (MCI) and dementia pose significant health challenges in aging societies, emphasizing the need for accessible, cost-effective, and noninvasive diagnostic tools. Electroencephalography (EEG) is a promising biomarker, but trad...
Advancing EEG based stress detection using spiking neural networks and convolutional spiking neural networks.
Scientific reports
Jul 19, 2025
Accurate and efficient analysis of Electroencephalogram (EEG) signals is crucial for applications like neurological diagnosis and Brain-Computer Interfaces (BCI). Traditional methods often fall short in capturing the intricate temporal dynamics inher...
EEG microstate analysis in children with prolonged disorders of consciousness.
Scientific reports
Jul 18, 2025
Prolonged disorders of consciousness (pDoC) in children lack objective and effective diagnostic methods to assess consciousness states, hindering targeted treatment selection and delaying recovery. It remains unclear whether EEG microstate analysis, ...
Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence.
NeuroImage
Jul 15, 2025
This comprehensive review examines the integration of Quantitative Electroencephalography (qEEG) and Artificial Intelligence (AI) in the detection and diagnosis of Alzheimer's Disease (AD). Through systematic analysis of 11 key studies across multipl...
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