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20142019
most citedSleep-wake classification via quantifying heart rate variability by convolutional neural network

59 citations · 88 across the 9 of their papers we have counts for

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eess.SP2019★ 9 cited

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…

eess.SP2019

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…