8 papers
Bio-Inspired Self-Supervised Learning for Wrist-worn Accelerometer Data
Prithviraj Tarale, Kiet Chu, Abhishek Varghese +4
Wearable accelerometers enable large-scale health monitoring, yet learning robust human-activity representations has been constrained by scarce labeled data. While self-supervised…
A Principle-Driven Adaptive Policy for Group Cognitive Stimulation Dialogue for Elderly with Cognitive Impairment
Jiyue Jiang, Yanyu Chen, Pengan Chen +7
Cognitive impairment is becoming a major public health challenge. Cognitive Stimulation Therapy (CST) is an effective intervention for cognitive impairment, but traditional methods…
MECKD: Deep Learning-Based Fall Detection in Multilayer Mobile Edge Computing With Knowledge Distillation
Wei-Lung Mao, Chun-Chi Wang, Po-Heng Chou +2
The rising aging population has increased the importance of fall detection (FD) systems as an assistive technology, where deep learning techniques are widely applied to enhance acc…
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…