Body Area Sensor Networks

Recent advancements in body area sensor networks (BASNs) have given rise to non-invasive systems that sense physiological, biokinetic, or ambient phenomena and use low-power radios to communicate information across the body. An example system with various physical and physiological sensor nodes and back-end servers is shown in the figure.

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BASNs show promise for use in a variety of applications (healthcare, entertainment, fitness, etc.). BASNs bare resemblance to wireless sensor networks (WSNs) more commonly researched, but some challenges specific to the body create a need for specialized BASN sensor node hardware and software beyond that of wireless “motes.” For instance, BASN nodes must be wearable with ergonomic design, small form factors, and consequently smaller batteries. At the same time, sensors in BASNs can operate at higher data rates than are seen in traditional WSNs creating the need for efficient tradeoffs between energy consumption and quality of service (QoS) (e.g. application fidelity, reliability, throughput, and latency). There are many BASN sensor platforms being developed today for both commercial and research purposes. Although networking in these systems may employ either mesh or star topologies, the limited number of nodes and small spatial diversity favor the latter.

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The INERTIA team researches the fundamental issues associated Body Area Sensor Networks (BASNs) including the tradeoffs associated with wearability, system capabilities, power consumption, dynamics environment adjustment, etc. Currently, a BASN system architecture is being designed that allows for dynamic calibration of data processing and transmission/storage to adjust for variable incoming data rates and dynamic wireless channel characteristics. The architecture shown below illustrates the use of both a data controller and a destination controller for runtime optimization of tradeoffs between power consumption, computational complexity, and signal fidelity. This system architecture is intended for implementation on resource constrained platforms common to BASN nodes.