AYLME — AI for Personalized Learning and Mind–Body Research
An adaptive, longitudinal approach to personal learning and mental well-being.
AYLME: A research and development initiative
AYLME is a YnnovScience R&D initiative to develop an AI system that learns about a person over time, identifies meaningful changes and provides insights and guidance tailored to individual needs.
The planned system integrates psychological measures, physiological data from wearable devices, behavioral information and personal context to build a dynamic, multidimensional picture.
The central innovation
Rather than detecting deviations from population averages alone, the proposed algorithm learns individual patterns, distinguishes natural fluctuations from meaningful changes and preserves information about trajectories over time. A central research challenge is controlling when and how a personal baseline is updated without losing significant changes.
Two complementary development paths
Personal application: A technology platform intended to identify needs and support mental well-being through tailored insights and guidance.
Mind–body research: A research infrastructure for examining dynamic relationships among physiology, psychological states and behavior.
Planned research architecture
Psychological self-reports and assessments, wearable physiological measurements, and behavioral/contextual information feed a longitudinal, adaptive AI engine. Potential outputs include personalized insights and research models that can be evaluated empirically.
Current development stage
Early research and development, measurement and monitoring infrastructure, and preparation for feasibility studies and algorithm validation. The proposed capabilities have not yet been scientifically validated; observed associations do not by themselves establish causation.