5 citations · 5 across the 6 of their papers we have counts for
6 papers
CAN-STRESS: A Real-World Multimodal Dataset for Understanding Cannabis Use, Stress, and Physiological Responses
Reza Rahimi Azghan, Nicholas C. Glodosky, Ramesh Kumar Sah +4
Coping with stress is one of the most frequently cited reasons for chronic cannabis use. Therefore, it is hypothesized that cannabis users exhibit distinct physiological stress res…
CUDLE: Learning Under Label Scarcity to Detect Cannabis Use in Uncontrolled Environments
Reza Rahimi Azghan, Nicholas C. Glodosky, Ramesh Kumar Sah +4
Wearable sensor systems have demonstrated a great potential for real-time, objective monitoring of physiological health to support behavioral interventions. However, obtaining accu…
Minimum-Cost Sensor Channel Selection For Wearable Computing
Ramesh Kumar Sah, Hassan Ghasemzadeh
Sensor systems are constrained by design and finding top sensor channel(s) for a given computational task is an important but hard problem. We define an optimization framework and…
ADARP: A Multi Modal Dataset for Stress and Alcohol Relapse Quantification in Real Life Setting
Ramesh Kumar Sah, Michael McDonell, Patricia Pendry +3
Stress detection and classification from wearable sensor data is an emerging area of research with significant implications for individuals' physical and mental health. In this wor…
Stress Classification and Personalization: Getting the most out of the least
Ramesh Kumar Sah, Hassan Ghasemzadeh
Stress detection and monitoring is an active area of research with important implications for the personal, professional, and social health of an individual. Current approaches for…
Adversarial Transferability in Wearable Sensor Systems
Ramesh Kumar Sah, Hassan Ghasemzadeh
Machine learning is used for inference and decision making in wearable sensor systems. However, recent studies have found that machine learning algorithms are easily fooled by the…