The convergence of artificial intelligence and wearable healthcare devices is revolutionizing patient care by enabling continuous monitoring, early disease detection, and personalized interventions. This presentation delves into the transformative potential of AI‑driven analytics in healthcare, focusing on real‑time physiological data processing to enhance decision‑making and improve patient outcomes.

We will explore key applications, including chronic disease management, mental health monitoring, and early warning systems for critical conditions. One notable application is in neurodiversity support, where AI‑powered wearables can analyze biometric and environmental data to predict sensory discomfort and panic attacks in autistic individuals. By monitoring physiological signals such as heart rate variability, sweating, and movement patterns alongside background noise levels, machine learning models can identify early indicators of distress. The system classifies sensory discomfort into different levels and provides real-time alerts, enabling caregivers to intervene proactively and create a more supportive environment.

Additionally, we will address challenges such as data privacy, algorithmic accuracy, and regulatory compliance in deploying AI‑powered healthcare solutions. Join this session to explore how AI and wearable technology are reshaping the healthcare landscape, paving the way for smarter, more inclusive, and proactive patient care.