Martin J. Cole

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Biomedical computing applications often require a computational pipeline that integrates data from experimental measurements or from image acquisition into a modeling and visualization environment. The latter process often involves segmentation, mesh generation, and numerical simulations. An important requirement of the numerical approximation and(More)
In this paper we introduce a numerical procedure for performing dynamic data driven simulations (DDDAS). The main ingredient of our simulation is the multiscale interpolation technique that maps the sensor data into the solution space. We test our method on various synthetic examples. In particular we show that frequent updating of the sensor data in the(More)
In this paper we evaluate different meshing schemes to solve for the bioelectric fields that arise in the human body due to the defibrillation shock generated by an Implantable Cardiac Defibrillator, with particular emphasis on implantation in children. For children, the question of relative performance of different electrode locations remains open.(More)
We describe a virtual telemetry system that allows us to devise and augment dynamic data-driven application simulations (DDDAS). Virtual telemetry has the advantage that it is inexpensive to produce from real time simulations and readily transmittable using open source streaming software. Real telemetry is usually expensive to receive (if it is even(More)
We describe how we plan to convert a traditional data collection sensor and ocean model into a DDDAS enabled system for identifying contaminants and then reacting with different models, simulations, and sensing strategies in a symbiotic manner. The sensor is just as useful in water as it would be on Mars for material identification. A successful terrestrial(More)
We describe, devise, and augment dynamic data-driven application simulations (DDDAS). DDDAS offers interesting computational and mathematically unsolved problems. In this paper, we discuss how to update the solution as well as input parameters involved in the simulation based on local measurements. The updates are performed in time. We test our method on(More)
We present an overview of an ongoing project to build a DDDAS for identifying and tracking chemicals in water. The project involves a new class of intelligent sensor, building a library to optically identify molecules, communication techniques for moving objects, and a problem solving environment. We are developing an innovative environment so that we can(More)
In this paper we discuss numerical techniques involved in dynamic data driven application simulations (DDDAS). We present an interpolation technique and update procedures. A multiscale interpolation technique is designed to map the sensor data into the solution space. In particular we show that frequent updating of the sensor data in the simulations can(More)
Computational modeling and simulation can provide important insights into the electrical and electrophysiological properties of cells, tissues, and organs. Commonly, the modeling is based on Maxwell's and Poisson's equations for electromagnetic and electric fields, respectively, and numerical techniques are applied for field calculation such as the finite(More)