AI-Driven Smart Wearables in Health and Sport Application
This dissertation presents a systematic review of smart wearable applications in sports and health, analyzing sensors, communication, algorithms, and evaluation schemes.
Overview
Building on this, we propose a unified three-layer pipeline that reconstructs incomplete data, personalizes multimodal physiological estimation, and enables efficient online prediction for real-time, energy-constrained wearable systems.
Presenters
Brief Biography
Luyao Yang is a Ph.D. candidate in Computer Science at the King Abdullah University of Science and Technology (KAUST) working in the Networking Research Lab (NETLAB) under Prof. Basem Shihada. She obtained her Bachelor's degree in Software Engineering at the University of Electronic Science and Technology of China and her Master's degree in Computer Science at King Abdullah University of Science and Technology.
