most citedTransfer Learning for Activity Recognition in Mobile Health

3 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20201 cited

Actionable Interpretation of Machine Learning Models for Sequential Data: Dementia-related Agitation Use Case

Nutta Homdee, John Lach

Machine learning has shown successes for complex learning problems in which data/parameters can be multidimensional and too complex for a first-principles based analysis. Some appl…

cs.LG20203 cited

Transfer Learning for Activity Recognition in Mobile Health

Yuchao Ma, Andrew T. Campbell, Diane J. Cook +6

While activity recognition from inertial sensors holds potential for mobile health, differences in sensing platforms and user movement patterns cause performance degradation. Aimin…

cs.CY20201 cited

MFED: A System for Monitoring Family Eating Dynamics

Md Abu Sayeed Mondol, Brooke Bell, Meiyi Ma +7

Obesity is a risk factor for many health issues, including heart disease, diabetes, osteoarthritis, and certain cancers. One of the primary behavioral causes, dietary intake, has p…

eess.SP2020

Wearable Respiration Monitoring: Interpretable Inference with Context and Sensor Biomarkers

Ridwan Alam, David B. Peden, John C. Lach

Breathing rate (BR), minute ventilation (VE), and other respiratory parameters are essential for real-time patient monitoring in many acute health conditions, such as asthma. The c…

cs.LG20192 cited

Enabling Smartphone-based Estimation of Heart Rate

Nutta Homdee, Mehdi Boukhechba, Yixue W. Feng +3

Continuous, ubiquitous monitoring through wearable sensors has the potential to collect useful information about users' context. Heart rate is an important physiologic measure used…