Optimal Design for Symbiotic Wearable Wireless Sensors

Sensors aesthetically embedded in accessories such as jewelry, piercings or contact lenses are being proposed recently. These symbiotic wearable wireless sensors are envisioned to operate on scarce harvested energy resources from the human body. In addition to the hardware and software constraints arising from the form-factor and low energy operations, there are safety requirements such as avoidance of physical injury. The design implications of these requirements are non-intuitive and may involve estimation of human physiological dynamics. The physical impact of a sensor operation can be controlled by appropriate design of multiple sensor components such as processor, radio, and optimization of data algorithm. For example, the risk of thermal injury to tissue can be reduced by limiting the sensing frequency, the computation power, and the radio duty cycle of body worn sensor. Hence, it is a challenging task to trace back a cause of a physical impact to hardware and software design decisions in a sensor. This paper proposes a novel non-linear optimization framework to consider safety and sustainability requirements that depend on the human physiology and derive system level design parameters of a sensor. We demonstrate our methodology using three case studies: a) continuously monitoring ECG sensor sustained by body heat, b) thermally safe network of implanted sensors, and c) infusion pump control algorithm to avoid hypoglycemia.