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Wallman M.,University of Oxford | Wallman M.,Fraunhofer Chalmers Center | Smith N.P.,University of Oxford | Smith N.P.,King's College London | Rodriguez B.,University of Oxford
Medical Image Analysis | Year: 2014

Cardiac imaging is routinely used to evaluate cardiac tissue properties prior to therapy. By integrating the structural information with electrophysiological data from e.g. electroanatomical mapping systems, knowledge of the properties of the cardiac tissue can be further refined. However, as in other clinical modalities, electrophysiological data are often sparse and noisy, and this results in high levels of uncertainty in the estimated quantities. In this study, we develop a methodology based on Bayesian inference, coupled with a computationally efficient model of electrical propagation to achieve two main aims: (1) to quantify values and associated uncertainty for different tissue conduction properties inferred from electroanatomical data, and (2) to design strategies to optimize the location and number of measurements required to maximize information and reduce uncertainty. The methodology is validated in an in silico study performed using simulated data obtained from a human image-based ventricular model, including realistic fibre orientation and a transmural scar. We demonstrate that the method provides a simultaneous description of clinically-relevant electrophysiological conduction properties and their associated uncertainty for various levels of noise. By using the developed methodology to investigate how the uncertainty decreases in response to added measurements, we then derive an a priori index for placing electrophysiological measurements in order to optimize the information content of the collected data. Results show that the derived index has a clear benefit in minimizing the uncertainty of inferred conduction properties compared to a random distribution of measurements, reducing the number of required measurements by over 50% in several of the investigated settings. This suggests that the methodology presented in this work provides an important step towards improving the quality of the spatiotemporal information obtained using electroanatomical mapping. © 2013 Elsevier B.V.


Wallman M.,University of Oxford | Smith N.P.,Fraunhofer Chalmers Center | Rodriguez B.,King's College London
IEEE Transactions on Biomedical Engineering | Year: 2012

The bidomain and monodomain equations are well established as the standard set of equations for the simulation of cardiac electrophysiological behavior. However, the computational cost of detailed bidomain/monodomain simulations limits their applicability in scenarios where a large number of simulations needs to be performed (e.g., parameter estimation). In this study, we present a graph-based method, which relies on point-to-point path finding to estimate activation times for single points in cardiac tissue with minimal computational costs. To validate our approach, activation times are compared to monodomain simulation results for an anatomically based rabbit ventricular model, incorporating realistic fiber orientation and conduction heterogeneities. Differences in activation times between the graph-based method and monodomain results are less than 10$\%$ of the total activation time, and computational performance is orders of magnitude faster with the proposed method when calculating activation times at single points. These results suggest that the graph-based method is well suited for estimating activation times when the need for fast performance justifies a limited loss of accuracy. © 1964-2012 IEEE.


Eriksson D.,Cornell University | Shellshear E.,Fraunhofer Chalmers Center
Graphical Models | Year: 2016

This paper describes a new efficient algorithm for the rapid computation of exact shortest distances between a point cloud and another object (e.g. triangulated, point-based, etc.) in three dimensions. It extends the work presented in Eriksson and Shellshear (2014) where only approximate distances were computed on a simplification of a massive point cloud. Here, the fast computation of the exact shortest distance is achieved by pruning large subsets of the point cloud known not to be closest to the other object. The approach works for massive point clouds even with a small amount of RAM and is able to provide real time performance. Given a standard PC with only 8GB of RAM, this resulted in real-time shortest distance computations of 15 frames per second for a point cloud having 1 billion points in three dimensions. © 2016 Elsevier Inc.


Hermansson T.,Fraunhofer Chalmers Center | Bohlin R.,Fraunhofer Chalmers Center | Carlson J.S.,Fraunhofer Chalmers Center | Soderberg R.,Chalmers University of Technology
Journal of Manufacturing Systems | Year: 2013

The automotive industry of today is becoming more focused on electrified and hybrid solutions, where both conventional combustion engines and battery supplied electrical engines need to fit in an already densely packed vehicle. Many quality problems are related do flexible parts. In particular, the assembly of electric cables and wiring harnesses is difficult due to its concealed routing, multiple branching points, weights and the flexibility in the material. To avoid late detection of assembly problems, the assembly aspect must be considered early during conceptual design and production preparation with respect to both feasibility and ergonomics. Development of automatic path planning methods in virtual manufacturing tools supporting deformable parts is therefore highly motivated. This article presents a novel method for automatically planning and finding a smooth and collision-free mounting of connectors in a wiring harness installation. Automatic path planning for deformable objects in general is widely acknowledged as a very difficult problem. To overcome this challenge, we propose a low-dimensional path planning algorithm that operates in the following way: constraint relaxation, handle path planning, unfolding, path smoothing and handle supplementation. The method has been implemented and successfully applied to an industrial test case. © 2013 The Society of Manufacturing Engineers.


Wallman M.,Fraunhofer Chalmers Center | Sandberg F.,Lund University
Computing in Cardiology | Year: 2016

Atrial fibrillation (AF) is a common and increasingly prevalent condition in the western society. During AF, the AV-node controls ventricular response to the rapid atrial impulses. However, current research indicates that the individual variability in AV-nodal function is large. Thus, characterization of the AV-node is an important step in determining the optimal form of treatment on an individual basis. Here we employ a multilevel modeling approach, comparing a previously presented statistical model with a novel detailed network model of the AV-nodal function during AF. We demonstrate that both models can be fitted to generate output that closely resembles clinical ECG data, and that estimated parameters in the less complex model corresponds to limited ranges of parameters in the more complex model. © 2015 CCAL.


Bjorkenstam S.,Fraunhofer Chalmers Center | Carlson J.S.,Fraunhofer Chalmers Center | Lennartson B.,Chalmers University of Technology
IEEE International Conference on Automation Science and Engineering | Year: 2015

The discrete equations of motion derived using a variational principle are particularly attractive to be used in numerical optimal control methods. This is mainly because: i) they exhibit excellent energy behavior, ii) they extend gracefully to systems with holonomic constraints and iii) they admit compact representation of the discrete state space. In this paper we propose the use of sparse finite differencing techniques for the Discrete Mechanics and Optimal Control method. In particular we show how to efficiently construct estimates of the Jacobian and Hessian matrices when the dynamics of the optimal control problem is discretized using a variational integrator. To demonstrate the effectiveness of this scheme we solve a human motion planning problem of an industrial assembly task, modeled as a multibody system consisting of more than one hundred degrees of freedom. © 2015 IEEE.


Anguelova M.,Imego AB | Karlsson J.,Fraunhofer Chalmers Center | Jirstrand M.,Fraunhofer Chalmers Center
Mathematical Biosciences | Year: 2012

Ordinary differential equation models in biology often contain a large number of parameters that must be determined from measurements by parameter estimation. For a parameter estimation procedure to be successful, there must be a unique set of parameters that can have produced the measured data. This is not the case if a model is not uniquely structurally identifiable with the given set of outputs selected as measurements. In designing an experiment for the purpose of parameter estimation, given a set of feasible but resource-consuming measurements, it is useful to know which ones must be included in order to obtain an identifiable system, or whether the system is unidentifiable from the feasible measurement set.We have developed an algorithm that, from a user-provided set of variables and parameters or functions of them assumed to be measurable or known, determines all subsets that when used as outputs give a locally structurally identifiable system and are such that any output set for which the system is structurally identifiable must contain at least one of the calculated subsets.The algorithm has been implemented in Mathematica and shown to be feasible and efficient. We have successfully applied it in the analysis of large signalling pathway models from the literature. © 2012 Elsevier Inc.


Almquist J.,Fraunhofer Chalmers Center | Wallman M.,Fraunhofer Chalmers Center | Wallman M.,University of Oxford | Jacobson I.,Astrazeneca | Jirstrand M.,Fraunhofer Chalmers Center
Biophysical Journal | Year: 2010

A wide range of ion channels have been considered as potential targets for pharmacological treatment of atrial fibrillation. The Kv1.5 channel, carrying the IKur current, has received special attention because it contributes to repolarization in the atria but is absent or weakly expressed in ventricular tissue. The dog serves as an important animal model for electrophysiological studies of the heart and mathematical models of the canine atrial action potential (CAAP) have been developed to study the interplay between ionic currents. To enable more-realistic studies on the effects of Kv1.5 blockers on the CAAP in silico, two continuous-time Markov models of the guarded receptor type were formulated for Kv1.5 and subsequently inserted into the Ramirez-Nattel-Courtemanche model of the CAAP. The main findings were: 1), time-and state-dependent Markov models of open-channel Kv1.5 block gave significantly different results compared to a time-and state-independent model with a downscaled conductance; 2), the outcome of Kv1.5 block on the macroscopic system variable APD90 was dependent on the precise mechanism of block; and 3), open-channel block produced a reverse use-dependent prolongation of APD90. This study suggests that more-complex ion-channel models are a prerequisite for quantitative modeling of drug effects. © 2010 by the Biophysical Society.


Eriksson D.,Fraunhofer Chalmers Center | Shellshear E.,Fraunhofer Chalmers Center
ICINCO 2014 - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics | Year: 2014

In this paper, algorithms have been developed that are capable of efficiently pre-processing massive point clouds for the rapid computation of the shortest distance between a point cloud and other objects (e.g. triangulated, point-based, etc.). This is achieved by exploiting fast distance computations between specially structured subsets of a simplified point cloud and the other object. This approach works for massive point clouds even with a small amount of RAM and was able to speed up the computations, on average, by almost two orders of magnitude. Given only 8 GB of RAM, this resulted in shortest distance computations of 30 frames per second for a point cloud originally having 1 billion points. The findings and implementations will have a direct impact for the many companies that want to perform path-planning applications through massive point clouds since the algorithms are able to produce real-time distance computations on a standard PC.


Shellshear E.,Fraunhofer Chalmers Center | Bohlin R.,Fraunhofer Chalmers Center
ICINCO 2014 - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics | Year: 2014

In this article we present a heuristic algorithm to compute the largest volume of an object in three dimensions that can move collision-free from a start configuration to a goal configuration through a virtual environment. The results presented here provide industrial designers with a framework to reduce the number of design iterations when designing parts to be placed in tight spaces.

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