Machine Learning-Based Indoor Health Monitoring Using a Dual-Band FR3 ISAC Prototype

Theme:

Signal Processing / Sensing

Application:

Health Monitoring

Contact Person:

Bixing Yan
Yang Miao

Intorduction:

The goal of this project is to design and evaluate machine-learning methods that combine information from communication and sensing channels to achieve robust indoor human monitoring.

Requirements:

Background in Electrical Engineering, Computer Science, or related fields
Basic knowledge of signal processing or wireless communications
Programming experience in Python and/or MATLAB
Interest in machine learning and hands-on experimental work
Curiosity about 6G, sensing, and real hardware systems

Additional Info