The field of wearable systems is moving towards proactive and personalized technologies that can adapt to individual users' needs and environments. Recent developments focus on leveraging artificial intelligence and machine learning to enhance human-machine interaction, improve responsiveness, and prioritize user privacy. Notable advancements include the integration of multi-modal sensor networks, edge-cloud collaborative computing, and hybrid approaches to data and knowledge modeling. These innovations aim to transition health management from passive monitoring to active collaborative evolution, emphasizing prevention, adaptability, and a harmonious relationship between technology and health management. Noteworthy papers include: Proactive Hearing Assistants that Isolate Egocentric Conversations, which introduces a proactive hearing assistant that automatically identifies and separates conversational partners. Artificial Intelligence-driven Intelligent Wearable Systems: A full-stack Integration from Material Design to Personalized Interaction, which presents a framework for integrating multi-modal sensor networks with edge-cloud collaborative computing and a hybrid approach to data and knowledge modeling.