Patients with chronic illness require frequent and avoidable hospital visits. This project aims to develop a new class of battery-less, low-cost, disposable, wireless electronic patch sensors to monitor a variety of physiological signals and a custom smartphone app to monitor their health status and to elect to share their anonymized events-of-interest with their community towards a smart and connected community (S&CC). To achieve these aims, the interdisciplinary research team is collaborating with the non-profit McKendree District of the United Methodist Church located in the greater Memphis community to complete this work. This will empower users, permit the community stakeholders to assess population health status, reduce the need for frequent hospital visits, and help identify potential individual and community actions to achieve improvement in health status. The project also involves the training of undergraduate and graduate students in interdisciplinary research activities on emerging technologies, and is expected to impact public and private sector efforts to improve healthcare.
A smart and connected community (S&CC) will utilize distributed sensors and embedded computing to seamlessly generate meaningful interpretations that would be of greater benefit to individuals, the community, and society, in general, through improved health and safety, efficient public infrastructure, and better access to needed services. Although rapidly emerging mobile health technology is already tapping into widely used smartphone infrastructure, data collection using smartphone mobile devices is currently limited by few integrated sensors (e.g., Inertial measurement unit (IMU), camera, optical sensors, temperature sensor, and GPS). There are tremendous opportunities to advance the smart and connected communities by incorporating capabilities from external battery-less sensors into this framework to enable data collection and analysis for broader personal and community gain. Towards this goal, this research will (1) deliver a platform of fully-passive wireless electronic patch sensors for physiological data collection and to incorporate multimodal sensor data, (2) develop an open-source framework for meaningful and reliable Events-of-Interest (EoI) detection using a custom smartphone app for self-monitoring and communal sharing, and (3) deploy the sensors in a "Living Lab" for a pilot study to collect and classify these data in real-time to generate EoIs for various health conditions, such as arrhythmia, asthma, and sleep disorder.
