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eess.SP2025

From High-SNR Radar Signal to ECG: A Transfer Learning Model with Cardio-Focusing Algorithm for Scenarios with Limited Data

Yuanyuan Zhang, Haocheng Zhao, Sijie Xiong +3

Electrocardiogram (ECG), as a crucial find-grained cardiac feature, has been successfully recovered from radar signals in the literature, but the performance heavily relies on the…

eess.SP2025

HEAR: An EEG Foundation Model with Heterogeneous Electrode Adaptive Representation

Zhige Chen, Chengxuan Qin, Wenlong You +5

Electroencephalography (EEG) is an essential technique for neuroscience research and brain-computer interface (BCI) applications. Recently, large-scale EEG foundation models have b…

eess.SP2025

radarODE-MTL: A Multi-Task Learning Framework with Eccentric Gradient Alignment for Robust Radar-Based ECG Reconstruction

Yuanyuan Zhang, Rui Yang, Yutao Yue +1

Millimeter-wave radar is promising to provide robust and accurate vital sign monitoring in an unobtrusive manner. However, the radar signal might be distorted in propagation by amb…

eess.SP2025

radarODE: An ODE-Embedded Deep Learning Model for Contactless ECG Reconstruction from Millimeter-Wave Radar

Yuanyuan Zhang, Runwei Guan, Lingxiao Li +3

Radar-based contactless cardiac monitoring has become a popular research direction recently, but the fine-grained electrocardiogram (ECG) signal is still hard to reconstruct from m…

eess.SP2024

EEGUnity: Open-Source Tool in Facilitating Unified EEG Datasets Towards Large-Scale EEG Model

Chengxuan Qin, Rui Yang, Wenlong You +4

The increasing number of dispersed EEG dataset publications and the advancement of large-scale Electroencephalogram (EEG) models have increased the demand for practical tools to ma…