3 papers
eess.SP2025
Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework
Cheol-Hui Lee, Hakseung Kim, Byung C. Yoon +1
Sleep is essential for maintaining human health and quality of life. Analyzing physiological signals during sleep is critical in assessing sleep quality and diagnosing sleep disord…
eess.SP2025
Diffusion-Based Electrocardiography Noise Quantification via Anomaly Detection
Tae-Seong Han, Jae-Wook Heo, Hakseung Kim +5
Electrocardiography (ECG) signals are frequently degraded by noise, limiting their clinical reliability in both conventional and wearable settings. Existing methods for addressing…
cs.HC2024
NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG
Cheol-Hui Lee, Hakseung Kim, Hyun-jee Han +3
The classification of sleep stages is a pivotal aspect of diagnosing sleep disorders and evaluating sleep quality. However, the conventional manual scoring process, conducted by cl…