Optimal design for symbiotic wearable wireless sensors

Sensors aesthetically embedded in accessoriessuch as jewelry, piercings or contact lenses arebeing proposed recently. These symbiotic wearable wirelesssensors are envisioned to operate on scarce harvestedenergy resources from the human body. In addition tothe hardware and software constraints arising from theform-factor and low energy operations, there are safetyrequirements such as avoidance of physical injury. Thedesign implications of these requirements are non-intuitiveand may involve estimation of human physiological dynamics. The physical impact of a sensor operation canbe controlled by appropriate design of multiple sensorcomponents such as processor, radio, and optimization ofdata algorithm. For example, the risk of thermal injury totissue can be reduced by limiting the sensing frequency, the computation power, and the radio duty cycle of bodyworn sensor. Hence, it is a challenging task to trace backa cause of a physical impact to hardware and softwaredesign decisions in a sensor. This paper proposes a novelnon-linear optimization framework to consider safety andsustainability requirements that depend on the humanphysiology and derive system level design parameters of asensor. We demonstrate our methodology using three casestudies: a) continuously monitoring ECG sensor sustainedby body heat, b) thermally safe network of implantedsensors, and c) infusion pump control algorithm to avoidhypo-glycemia.