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 wire- less 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.
Advances in flexible ultra low power electronics have resulted in prototypes of new age non-invasive symbiotic sensors that can be embedded in accessories such as contact lenses and body piercings. They are envisioned to operate using energy scavenged from the human body. Such sensors when supplemented with continuous communication capabilities can be used for non-invasive ”smart” behavioral monitoring.
However, a significant issue for wearable sensors, which has received limited focus, is their interaction with the human body that can have serious implications on the sensor hardware and software design.
Currently the impact of a certain hardware or software design decision on the human body is done by modelling with complex differential equations and using state of the art simulators. This paper considers the reverse: finding the implications of physiology dependent system requirements such as user safety on the sensor design aspects. This is a far more challenging problem since the design implications can pervade over several system components.
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 hypo-glycemia.
To read this external content in full, download the complete paper from the author archives online at Arizona State University.
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