Understanding human activity and behavior is an important problem in wearable computing and has the potential to unlock many possibilities in health monitoring. Real-time stress detection and monitoring is another important challenge that can help us understand and propose solutions to problems such as alcohol addiction. Sensor data obtained for different biomarkers such as heart rate and body acceleration is given as input to machine learning algorithms to learn the relationship between physiological events in the human body. Actionable outcomes in real life such as listening to music for stress management and optimal time for medication adherence can then be guided using the outcome of trained machine learning models. The guest speaker will discuss research problems and explain studies designed to answer important questions in stress monitoring and human activity recognition.

Zoom information:
https://wsu.zoom.us/j/94055754369?pwd=STFWMzFyRXlXMEh4UlU5MUw1dFVHQT09

Meeting ID: 940 5575 4369
Passcode: 011796