This $350,000 federal Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports the development of intelligent anonymization methods to preserve the privacy of clients' bio-signals while retaining data utility for clinical purposes.
The project at the University of California, Irvine aims to create modular and scalable anonymization models that can be customized for diverse client demographics and health conditions. This will enable the generation of anonymized multi-channel bio-signals through reinforcement learning-guided generative deep models. The project also develops a privacy assessment and evaluation framework to update the anonymization models based on utility and anonymity metrics. The goal is to foster patient participation in healthcare and research studies without fear of identity exposure, thereby enabling the development of efficient data-driven AI models for smart healthcare.
Generated 3/4/25, 6:05 AM