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Found 5 papers, 0 papers with code
Graph Convolutional Network with Connectivity Uncertainty for EEG-based Emotion Recognition
To address these challenges, this study introduces the distribution-based uncertainty method to represent spatial dependencies and temporal-spectral relativeness in EEG signals based on Graph Convolutional Network (GCN) architecture that adaptively assigns weights to functional aggregate node features, enabling effective long-path capturing while mitigating over-smoothing phenomena.
ECG-CL: A Comprehensive Electrocardiogram Interpretation Method Based on Continual Learning
From the perspective of intelligent wearable applications, the possibility of a comprehensive ECG interpretation algorithm based on single-lead ECGs is also confirmed.
A Causal Intervention Scheme for Semantic Segmentation of Quasi-periodic Cardiovascular Signals
To address this issue, we establish a structural causal model as the foundation to customize the intervention approaches on Am and Ar, respectively.
Temporal-Framing Adaptive Network for Heart Sound Segmentation without Prior Knowledge of State Duration
Moreover, the TFAN-based method achieved an overall F1 score of 99. 2%, 94. 4%, 91. 4% on LEVEL-I, -II and -III data respectively, compared to 98. 4%, 88. 54% and 79. 80% for the current state-of-the-art method.
An Open Access Database for Evaluating the Algorithms of Electrocardiogram Rhythm and Morphology Abnormality Detection
Over the past few decades, methods for classification and detection of rhythm or morphology abnormalities in ECG signals have been widely studied.
