SCH: Next-Generation Multimodal Wearable Sensing and Integrative AI Systems for Precision COPD Risk Prediction and Clinical Decision Support - PROJECT SUMMARY (See instructions): This project advances NHLBI's priorities in health equity, lung disease prevention, and precision medicine by delivering an AI-enabled platform that reduces COPD (Chronic Obstructive Pulmonary Disease) exacerbations, narrows respiratory health disparities, and is designed for national scalability. COPD affects approximately 16 million Americans, is the fourth leading cause of death, and costs an estimated $50 billion annually, with the burden falling disproportionately on under-resourced and environmentally burdened communities where real-time linkages between environmental exposures and clinical decision-making remain severely limited. The long-term objectives, achieved through five specific aims — (1) WSU engineering and optimization; (2) patient-centered monitoring and clinical integration; (3) environmental data fusion and bias correction; (4) AI-powered advisory system (AQA-AI) development; and (5) translating innovation to sustainable impact — are to develop, validate, and deploy a scalable precision health infrastructure integrating next-generation wearable sensing, satellite-derived environmental data, and adaptive AI. The WSU — a miniaturized, multimodal, ultra-low-power device — continuously monitors respiratory physiology and environmental exposures in n=100 COPD patients across two seasonal monitoring periods. WSU data are fused with satellite observations (MODIS, TROPOMI) and ground-based networks to generate individual-level, bias-corrected exposure surfaces that feed deep learning models (LSTM, graph neural networks) to produce exacerbation risk forecasts, interpretable clinical alerts, and personalized guidance in near real time. Memphis, Tennessee, serves as the initial testbed; the platform is expressly designed for scalability to additional respiratory conditions and diverse U.S. settings. Validation proceeds across three phases: WSU hardware refinement and accuracy testing; prospective evaluation against clinical endpoints, including exacerbations and hospitalizations; and implementation science-guided deployment (CFIR, RE-AIM) to ensure sustained clinical use. The platform is transferable to asthma, interstitial lung disease, and other respiratory conditions, engaging patients, clinicians, and community members from diverse and underrepresented backgrounds throughout.
