12 citations · 36 across the 15 of their papers we have counts for
16 papers
Loneliness Forecasting Using Multi-modal Wearable and Mobile Sensing in Everyday Settings
Zhongqi Yang, Iman Azimi, Salar Jafarlou +7
The adverse effects of loneliness on both physical and mental well-being are profound. Although previous research has utilized mobile sensing techniques to detect mental health iss…
Enhancing Performance and User Engagement in Everyday Stress Monitoring: A Context-Aware Active Reinforcement Learning Approach
Seyed Amir Hossein Aqajari, Ziyu Wang, Ali Tazarv +6
In today's fast-paced world, accurately monitoring stress levels is crucial. Sensor-based stress monitoring systems often need large datasets for training effective models. However…
Integrating Wearable Sensor Data and Self-reported Diaries for Personalized Affect Forecasting
Zhongqi Yang, Yuning Wang, Ken S. Yamashita +6
Emotional states, as indicators of affect, are pivotal to overall health, making their accurate prediction before onset crucial. Current studies are primarily centered on immediate…
Context-Aware Stress Monitoring using Wearable and Mobile Technologies in Everyday Settings
Seyed Amir Hossein Aqajari, Sina Labbaf, Phuc Hoang Tran +5
Daily monitoring of stress is a critical component of maintaining optimal physical and mental health. Physiological signals and contextual information have recently emerged as prom…
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…
ZotCare: A Flexible, Personalizable, and Affordable mHealth Service Provider
Sina Labbaf, Mahyar Abbasian, Iman Azimi +2
The proliferation of Internet-connected health devices and the widespread availability of mobile connectivity have resulted in a wealth of reliable digital health data and the pote…
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…
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…
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…
Hybrid Learning for Orchestrating Deep Learning Inference in Multi-user Edge-cloud Networks
Sina Shahhosseini, Tianyi Hu, Dongjoo Seo +4
Deep-learning-based intelligent services have become prevalent in cyber-physical applications including smart cities and health-care. Collaborative end-edge-cloud computing for dee…
Online Learning for Orchestration of Inference in Multi-User End-Edge-Cloud Networks
Sina Shahhosseini, Dongjoo Seo, Anil Kanduri +5
Deep-learning-based intelligent services have become prevalent in cyber-physical applications including smart cities and health-care. Deploying deep-learning-based intelligence nea…
Objective Prediction of Tomorrow's Affect Using Multi-Modal Physiological Data and Personal Chronicles: A Study of Monitoring College Student Well-being in 2020
Salar Jafarlou, Jocelyn Lai, Zahra Mousavi +5
Monitoring and understanding affective states are important aspects of healthy functioning and treatment of mood-based disorders. Recent advancements of ubiquitous wearable technol…
Novel Blood Pressure Waveform Reconstruction from Photoplethysmography using Cycle Generative Adversarial Networks
Milad Asgari Mehrabadi, Seyed Amir Hossein Aqajari, Amir Hosein Afandizadeh Zargari +2
Continuous monitoring of blood pressure (BP)can help individuals manage their chronic diseases such as hypertension, requiring non-invasive measurement methods in free-living condi…
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…
Data Collection and Labeling of Real-Time IoT-Enabled Bio-Signals in Everyday Settings for Mental Health Improvement
Ali Tazarv, Sina Labbaf, Amir M. Rahmani +2
Real-time physiological data collection and analysis play a central role in modern well-being applications. Personalized classifiers and detectors have been shown to outperform gen…
Personalized Stress Monitoring using Wearable Sensors in Everyday Settings
Ali Tazarv, Sina Labbaf, Stephanie M. Reich +3
Since stress contributes to a broad range of mental and physical health problems, the objective assessment of stress is essential for behavioral and physiological studies. Although…