Mental Health

A comprehensive review on AI-powered wearable biosensors, highlighting how machine learning and edge AI enable real-time health monitoring and personalized care. The paper discusses key innovations like digital twins and LLMs, along with challenges in privacy, scalability, and clinical integration..

This paper introduces a multimodal blood glucose forecasting framework that combines time-aware cross-attention with an LSTM to predict glucose levels from CG) data and complementary wearable signals (heart rate, EDA, accelerometry, and diet).