SHADE-AD is a pioneering framework that leverages large language models to synthesize realistic activity data of Alzheimer's patients, addressing a critical gap in developing smart health monitoring solutions.

• Creates privacy-preserving synthetic datasets that mimic AD patient behaviors
• Combines insights from public datasets and newly collected data to train the LLM framework
• Enables development and testing of monitoring solutions without extensive real patient data collection
• Accelerates research in smart health applications for Alzheimer's care

This innovation matters because it can dramatically speed up the development of AI monitoring systems for Alzheimer's patients, potentially improving quality of care while reducing the burden on caregivers and healthcare systems.

SHADE-AD: An LLM-Based Framework for Synthesizing Activity Data of Alzheimer's Patients