Pharma LPII-Wearable Intelligence for Everyday Wellness and Stress Monitoring
This project investigates how wearable devices, such as smart earrings, rings, and glasses, can combine behavioral and physiological sensing to understand everyday wellness and stress. Students will use existing wearable platforms to capture signals related to head posture and motion, body posture and body language, social interactions, and physiological responses to stress.
Faculty Advisor:
Description:
This project investigates how wearable devices, such as smart earrings, rings, and glasses, can combine behavioral and physiological sensing to understand everyday wellness and stress. Students will use existing wearable platforms to capture signals related to head posture and motion, body posture and body language, social interactions, and physiological responses to stress. Students will design and conduct data collection studies, analyze and visualize multimodal sensor data, and develop machine learning models that integrate behavioral and physiological signals to estimate and understand users’ wellness and stress in everyday settings. Through this project, students will gain hands-on experience with the complete wearable-intelligence pipeline, from analyzing real-world data to developing AI models for continuous and unobtrusive wellness monitoring.
Prerequisites:
- Required: Basic programming experience, machine learning/deep learning.
- Good to have: Human-computer interaction, signal processing, physiological sensing, embedded or wearable systems.
- Students from Computer Science, Electrical and Computer Engineering, Data Science, Biomedical Engineering, and related disciplines are especially encouraged to participate. Students from other majors with an interest in wearable technology and digital health are also welcome.