#eeg
5 papers match
Toward Annotation-Efficient Continuous Emotion Arousal Quantification via Group-Level EEG Dynamic Neural Synchrony
Guandong Pan, Yaqian Yang, Shi Chen +4
The paper proposes using group-level EEG dynamic neural synchrony as a signal to continuously quantify emotional arousal without needing per‑subject manual annotations, showing tha…
EEG-based AI-BCI Wheelchair Advancement: Transformer-Based Learning with Motor Imagery for Brain Computer Interface
Bipul Thapa, Biplov Paneru, Bishwash Paneru +1
The paper proposes a Transformer‑based deep learning model (TFormerEEG) to classify motor‑imagery EEG signals for controlling a simulated wheelchair, achieving over 90% accuracy.
AnySleep: a channel-agnostic deep learning system for high-resolution sleep staging in multi-center cohorts
Niklas Grieger, Jannik Raskob, Siamak Mehrkanoon +1
AnySleep is a deep learning system that automatically stages sleep using EEG or EOG data at flexible time resolutions, and it works well across many clinical sites and electrode se…
Learning Residual Kinematic Corrections for Continuous Neural Decoding via Reinforcement Learning
Jiamian Li, Niall McShane, Attila Korik +6
The paper introduces a two‑stage framework that uses reinforcement learning to correct residual errors in continuous 3‑D motor‑imagery decoding from EEG, improving accuracy over a…
DiffEEG: A Self-Supervised Denoising Diffusion Model for Learning EEG Generic Representations
Abdulkader Helwan, Lina Abou-Abbas, Hussein El Amouri +2
The paper introduces DiffEEG, a self‑supervised diffusion model that learns generic EEG representations from millions of unlabeled recordings and fine‑tunes them with reinforcement…