Artificial Intelligence-Driven Resilient Health and Biological Systems (AI-ReHaB 2024)

AI-ReHaB focuses on integrating AI technologies into research on sensing systems for health and biological systems, especially biomonitoring devices. Our goal is to improve the data quality, develop quantification algorithms, secure the devices from external attacks, and optimize the devices for end users. Along with research activities, knowledge-broadening lectures are planned to teach students about current AI techniques and their application in the health sector.

Research areas:

  • To investigate novel optical device architectures with thin film electronics for spectroscopic detection through AI.
  • Explore the fusion of multiple biosensing modalities (ECG, SCG, PPG, NIRS, etc.) toward understanding cardiac diseases.
  • Examine the fusion of motion data from inertial sensors, temperature, oxygenation, etc. toward improving rehabilitation and athletic training.
  • To create and test sensors for fNIRS, ECG, and EOG for real-world scenarios to evaluate mental fatigue.
  • To develop sensors to monitor animal behavior, understand their impact on local biodiversity, and map climate change

For further information on AI-ReHaB, please visit the following website:

AI-ReHaB website link