Using Embedded Sensors in Smartphones to Monitor and Detect Early Symptoms of Exercise-induced Asthma

摘要

This paper describes work in progress on integrated design architecture for monitoring and detecting early symptoms of asthma attack using smartphone as sensors' platform for data capturing, processing, presentation and feedback. We present an application scenario of exercise-induced asthma where a patient wears a smartphone equipped with built-in sensors which are capable of providing clinical data and context on detection of any anomaly in the monitored vital signs. Our design architecture extends the functionality of "Nine-degree of Freedom" (9-DoF) sensor fusion model and context recognition using expert system frameworks. The design centers on the idea of creating a simple and portable asthma monitoring system that is able to detect asthma vital signs, perform signal analysis and context generation; and also send information to other mobile devices worn by caregivers and physicians. This approach removes the need to have external monitoring sensors patched on the user's body, thereby enhancing the usability and reliability of the system in providing timely information on the state of a patient's health.