59 citations · 88 across the 9 of their papers we have counts for
9 papers
A persistent homology approach to heart rate variability analysis with an application to sleep-wake classification
Yu-Min Chung, Chuan-Shen Hu, Yu-Lun Lo +1
Persistent homology (PH) is a recently developed theory in the field of algebraic topology to study shapes of datasets. It is an effective data analysis tool that is robust to nois…
Explore intrinsic geometry of sleep dynamics and predict sleep stage by unsupervised learning techniques
Gi-Ren Liu, Yu-Lun Lo, Yuan-Chung Sheu +1
We propose a novel unsupervised approach for sleep dynamics exploration and automatic annotation by combining modern harmonic analysis tools. Specifically, we apply diffusion-based…
Unexpected sawtooth artifact in beat-to-beat pulse transit time measured from patient monitor data
Yu-Ting Lin, Yu-Lun Lo, Chen-Yun Lin +2
Object: It is increasingly popular to collect as much data as possible in the hospital setting from clinical monitors for research purposes. However, in this setup the data calibra…
Sleep-wake classification via quantifying heart rate variability by convolutional neural network
John Malik, Yu-Lun Lo, Hau-tieng Wu
Fluctuations in heart rate are intimately tied to changes in the physiological state of the organism. We examine and exploit this relationship by classifying a human subject's wake…
Diffuse to fuse EEG spectra -- intrinsic geometry of sleep dynamics for classification
Gi-Ren Liu, Yu-Lun Lo, John Malik +2
We propose a novel algorithm for sleep dynamics visualization and automatic annotation by applying diffusion geometry based sensor fusion algorithm to fuse spectral information fro…
Phenotype-based and Self-learning Inter-individual Sleep Apnea Screening with a Level IV Monitoring System
Hau-Tieng Wu, Jhao-Cheng Wu, Po-Chiun Huang +4
Purpose: We propose a phenotype-based artificial intelligence system that can self-learn and is accurate for screening purposes, and test it on a Level IV monitoring system. Method…
Diffusion-based nonlinear filtering for multimodal data fusion with application to sleep stage assessment
Ori Katz, Ronen Talmon, Yu-Lun Lo +1
The problem of information fusion from multiple data-sets acquired by multimodal sensors has drawn significant research attention over the years. In this paper, we focus on a parti…
Sleep Apnea Detection Based on Thoracic and Abdominal Movement Signals of Wearable Piezo-Electric Bands
Yin-Yan Lin, Hau-tieng Wu, Chi-An Hsu +3
Physiologically, the thoracic (THO) and abdominal (ABD) movement signals, captured using wearable piezo-electric bands, provide information about various types of apnea, including…
Assess Sleep Stage by Modern Signal Processing Techniques
Hau-tieng Wu, Ronen Talmon, Yu-Lun Lo
In this paper, two modern adaptive signal processing techniques, Empirical Intrinsic Geometry and Synchrosqueezing transform, are applied to quantify different dynamical features o…