Cardiovascular disease (CVD) threatens the lives of many and affects their productivity. Wearable sensors can enable continuous monitoring of hemodynamic parameters to improve the diagnosis and management of CVD. Bio-Impedance (Bio-Z) is an effective non-invasive sensor for arterial pulse wave monitoring based on blood volume changes in the artery due to the deep penetration of its current signal inside the tissue. However, the measured data are significantly affected by the placement of electrodes relative to the artery and the electrode configuration. In this work, we created a Bio-Z simulation platform that models the tissue, arterial pulse wave, and Bio-Z sensing configuration using a 3D circuit model based on a time-varying impedance grid. A new method is proposed to accurately simulate the different tissue types such as blood, fat, muscles, and bones in a 3D circuit model in addition to the pulsatile activity of the arteries through a variable impedance model. This circuit model is simulated in SPICE and can be used to guide design decisions (i.e. electrode placement relative to the artery and electrode configuration) to optimize the monitoring of pulse wave prior to experimentation. We present extensive simulations of the arterial pulse waveform for different sensor locations, electrode sizes, current injection frequencies, and artery depths. These simulations are validated by experimental Bio-Z measurements.

TerraSwarm applications, or swarmlets, are characterized by their ability to dynamically recruit resources such as sensors, communication networks, computation, and information from the cloud; to aggregate and use that information to make or aid decisions; and then to dynamically recruit actuation resources. The TerraSwarm vision cannot be achieved by a single vendor providing the components as an integrated system. What is needed instead is the swarm equivalent of the common, general framework that has recently enabled smartphones and similar devices to rapidly deploy and serve a vast range of often unanticipated applications by recruiting resources and composing services. The SwarmOS must support continual reconfiguration of applications and of its own service definitions without ever having the luxury of a clean restart. It must also support richly heterogeneous computing. TerraSwarm protocols will need to detect compromises, distinguish trusted from untrusted data and resources, and be robust to the presence of a certain number of malicious nodes.