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20212023
most citedActive Reinforcement Learning for Personalized Stress Monitoring in Everyday Settings

12 citations · 14 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.LG2023

Reducing Intraspecies and Interspecies Covariate Shift in Traumatic Brain Injury EEG of Humans and Mice Using Transfer Euclidean Alignment

Manoj Vishwanath, Steven Cao, Nikil Dutt +3

While analytics of sleep electroencephalography (EEG) holds certain advantages over other methods in clinical applications, high variability across subjects poses a significant cha…

cs.LG202312 cited

Active Reinforcement Learning for Personalized Stress Monitoring in Everyday Settings

Ali Tazarv, Sina Labbaf, Amir Rahmani +2

Most existing sensor-based monitoring frameworks presume that a large available labeled dataset is processed to train accurate detection models. However, in settings where personal…

cs.LG2022

Edge-centric Optimization of Multi-modal ML-driven eHealth Applications

Anil Kanduri, Sina Shahhosseini, Emad Kasaeyan Naeini +4

Smart eHealth applications deliver personalized and preventive digital healthcare services to clients through remote sensing, continuous monitoring, and data analytics. Smart eHeal…

cs.LG20221 cited

Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing

Sina Shahhosseini, Yang Ni, Hamidreza Alikhani +4

Health monitoring applications increasingly rely on machine learning techniques to learn end-user physiological and behavioral patterns in everyday settings. Considering the signif…

cs.LG20211 cited

AMSER: Adaptive Multi-modal Sensing for Energy Efficient and Resilient eHealth Systems

Emad Kasaeyan Naeini, Sina Shahhosseini, Anil Kanduri +3

eHealth systems deliver critical digital healthcare and wellness services for users by continuously monitoring physiological and contextual data. eHealth applications use multi-mod…