7 citations · 9 across the 9 of their papers we have counts for
6 papers · 1 filter
MSECG: Incorporating Mamba for Robust and Efficient ECG Super-Resolution
Jie Lin, I Chiu, Kuan-Chen Wang +4
Electrocardiogram (ECG) signals play a crucial role in diagnosing cardiovascular diseases. To reduce power consumption in wearable or portable devices used for long-term ECG monito…
MSEMG: Surface Electromyography Denoising with a Mamba-based Efficient Network
Yu-Tung Liu, Kuan-Chen Wang, Rong Chao +3
Surface electromyography (sEMG) recordings can be contaminated by electrocardiogram (ECG) signals when the monitored muscle is closed to the heart. Traditional signal processing-ba…
TrustEMG-Net: Using Representation-Masking Transformer with U-Net for Surface Electromyography Enhancement
Kuan-Chen Wang, Kai-Chun Liu, Ping-Cheng Yeh +2
Surface electromyography (sEMG) is a widely employed bio-signal that captures human muscle activity via electrodes placed on the skin. Several studies have proposed methods to remo…
MECG-E: Mamba-based ECG Enhancer for Baseline Wander Removal
Kuo-Hsuan Hung, Kuan-Chen Wang, Kai-Chun Liu +4
Electrocardiogram (ECG) is an important non-invasive method for diagnosing cardiovascular disease. However, ECG signals are susceptible to noise contamination, such as electrical i…
SDEMG: Score-based Diffusion Model for Surface Electromyographic Signal Denoising
Yu-Tung Liu, Kuan-Chen Wang, Kai-Chun Liu +2
Surface electromyography (sEMG) recordings can be influenced by electrocardiogram (ECG) signals when the muscle being monitored is close to the heart. Several existing methods use…
A Non-Intrusive Neural Quality Assessment Model for Surface Electromyography Signals
Cho-Yuan Lee, Kuan-Chen Wang, Kai-Chun Liu +4
In practical scenarios involving the measurement of surface electromyography (sEMG) in muscles, particularly those areas near the heart, one of the primary sources of contamination…