SCH: Bringing Intelligence to Pulmonology: New AI-Enabled Systems for Pulmonary Function Tests Anytime and Anywhere

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Pulmonary diseases constitute a major public health challenge, and pulmonary function testing (PFT) is the main method of evaluating the changes in human airway mechanics, which are the key symptoms of pulmonary diseases. Due to the possibility of frequent exacerbations in pulmonary diseases, it is important that PFT is accessible to patients anytime and anywhere out of clinic, but most of current in-clinic PFT techniques are too cumbersome and expensive to be used out of clinic. This project addresses these challenges to enable PFT anytime and anywhere, by developing new and integrated artificial intelligence (AI) and sensing systems on commodity smartphones. As pulmonary diseases widely affect the human society and result in billions of annual healthcare related costs, this project has great potential to benefit society by enabling efficient disease monitoring, diagnosis and management out of clinic. This project is also contributing to society by producing datasets that help understand the disease mechanisms, as well as developing new curricula, disseminating research for education and training, and engaging underrepresented students in research.The primary goal of this project is to enable highly accurate, adaptable and generic PFT out of clinic using commodity smartphones. The project consists of four research tasks: (1) designing new acoustic sensing systems on commodity smartphones that measure the humans’ airway lumen dimensions and characteristics; (2) extracting appropriate biomarker profiles from acoustic sensory data for disease evaluation; (3) developing generalizable machine learning (ML) models that can be applied to evaluating different pulmonary diseases; (4) exploring distributed and asynchronous methods of training the ML models with new federated learning techniques.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.