6 citations · 13 across the 5 of their papers we have counts for
5 papers
PiRL: Participant-Invariant Representation Learning for Healthcare
Zhaoyang Cao, Han Yu, Huiyuan Yang +1
Due to individual heterogeneity, performance gaps are observed between generic (one-size-fits-all) models and person-specific models in data-driven health applications. However, in…
Empirical Evaluation of Data Augmentations for Biobehavioral Time Series Data with Deep Learning
Huiyuan Yang, Han Yu, Akane Sano
Deep learning has performed remarkably well on many tasks recently. However, the superior performance of deep models relies heavily on the availability of a large number of trainin…
Semi-Supervised Learning and Data Augmentation in Wearable-based Momentary Stress Detection in the Wild
Han Yu, Akane Sano
Physiological and behavioral data collected from wearable or mobile sensors have been used to estimate self-reported stress levels. Since the stress annotation usually relies on se…
More to Less (M2L): Enhanced Health Recognition in the Wild with Reduced Modality of Wearable Sensors
Huiyuan Yang, Han Yu, Kusha Sridhar +3
Accurately recognizing health-related conditions from wearable data is crucial for improved healthcare outcomes. To improve the recognition accuracy, various approaches have focuse…
Forecasting Health and Wellbeing for Shift Workers Using Job-role Based Deep Neural Network
Han Yu, Asami Itoh, Ryota Sakamoto +2
Shift workers who are essential contributors to our society, face high risks of poor health and wellbeing. To help with their problems, we collected and analyzed physiological and…