Lifetime Improvement in Body Sensor Networks

Shakhsheer, Yousef, Electrical Engineering - School of Engineering and Applied Science, University of Virginia
Calhoun, Benton, Department of Electrical and Computer Engineering, University of Virginia

Body sensor networks (BSNs) promise to provide significant benefits to the healthcare domain. BSNs consist of multiple nodes that sense, process, and transmit health data and an aggregator that manages nodes, processes data, and passes information between the nodes and the base station. Though BSNs have tremendous potential for improving health care, their practical adoption must overcome technical and social challenges such as form factor, battery life, and reliability. BSN nodes will not be adopted if they are unsightly, large and bulky, or require frequent battery changes or charging. The focus of this work is to improve BSN node and aggregator lifetime to improve the overall BSN lifetime. Improved BSN lifetime will augment remote, long-term monitoring of chronically-ill patients, firefighters, and athletes.

The most desirable BSN lifetime is an infinite device lifetime; battery power constrains the lifetime of the device to a finite period of time. Energy harvesting mechanisms such as solar power, thermoelectric generation, and piezoelectric provide an alternative power source to these energy constrained devices for the possibility of infinite device lifetime. For a desired BSN node form factor of less than 1cm^3, energy harvesting mechanisms can produce 50-100µWs. With careful design and tight system integration, BSN nodes can achieve this power consumption and potentially achieve an indefinite lifetime. This work presents the first wireless biosignal acquisition chip powered solely from a thermoelectric harvester and/or RF power with integrated supply regulation, analog front end, power management, subthreshold digital signal processing, and a transmitter. This work also investigates BSN architecture decisions such as tradeoffs between custom controllers and generic microcontrollers, to inform future designs. Additionally, this work demonstrates the first-implemented on-chip, closed-loop power management system capable of adjusting node power consumption to the amount of energy harvested and explores the power management design space.

Aggregators cannot operate exclusively from energy harvesting due to their high processing/communication requirements and the inability to harvest a sufficient amount of energy. Therefore, the aggregator has become the determining factor in the BSN’s lifetime. To extend lifetime of the aggregator and the whole BSN, we can leverage the aggregator's variable workload to improve battery lifetime by applying a fine-grained dynamic voltage scaling (DVS) scheme; this workload changes with amount of data that needs to be processed and the number of nodes with which are being communicated. This method, called Panoptic ("all-inclusive") Dynamic Voltage Scaling (PDVS), extends DVS to a finer granularity in space and time, allowing for much more flexible and energy efficient design and therefore a longer battery lifetime for the aggregator and a longer lifetime for the system. This work applies PDVS to a DSP data-flow processor as a proof of concept to show energy savings over multiple benchmark workloads and characterizes the overheads of PDVS.

PHD (Doctor of Philosophy)
Body Sensor Networks, BSNs, PDVS, energy harvesting, ultra low power
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