6 papers
Robust Photoplethysmography Signal Denoising via Mamba Networks
I Chiu, Yu-Tung Liu, Kuan-Chen Wang +2
Photoplethysmography (PPG) is widely used in wearable health monitoring, but its reliability is often degraded by noise and motion artifacts, limiting downstream applications such…
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…
Transfer Learning for Keypoint Detection in Low-Resolution Thermal TUG Test Images
Wei-Lun Chen, Chia-Yeh Hsieh, Yu-Hsiang Kao +3
This study presents a novel approach to human keypoint detection in low-resolution thermal images using transfer learning techniques. We introduce the first application of the Time…
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…
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…
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…