Toward Breath Sensors That Are Self-Powered by Design

Piezoelectric materials are widely used to generate electric charge from mechanical deformation or vice versa. These strategies are increasingly common in implantable medical devices, where sensing must be done on small scales. In the case of a flow rate sensor, a sensor’s energy harvesting rate could be mapped to that flow rate, making it “Self-Powered by Design (SPD)”. Prior fluids-based SPD work has focused on turbulence-driven resonance and has been largely empirical. In this dissertation, I explore sub-resonance SPD sensing via a case study of human breathing. I present a model of self-powered piezoelectric sensing/harvesting and validate that model against experimental results, both in vitro and in vivo. This work offers a form of SPD sensing that scales down to micro- or nano-scales, where flows are locally laminar and wake-driven resonance is not an option, and offers a model-based roadmap for future SPD sensing solutions. I use this model to theorize and test a new form of SPD sensing that can detect broadband flow information and to explore the effects of physical scale on sensor/harvester effectiveness, while also lending my experimental platform and modeling experience to other collaborative, biomedically-focused studies.