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Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware

Bodisco, Timothy, D'Netto, Jason, Kelson, Neil, Banks, Jasmine and Hayward, Ross 2014, Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware, Procedia computer science, vol. 29, Proceedings of 14th International Conference on Computational Science, pp. 2442-2448, doi: 10.1016/j.procs.2014.05.228.

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Title Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware
Author(s) Bodisco, TimothyORCID iD for Bodisco, Timothy orcid.org/0000-0002-5163-4762
D'Netto, Jason
Kelson, Neil
Banks, Jasmine
Hayward, Ross
Journal name Procedia computer science
Volume number 29
Season Proceedings of 14th International Conference on Computational Science
Start page 2442
End page 2448
Total pages 7
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2014
ISSN 1877-0509
Keyword(s) ECG signal analysis
Markov-chain Monte Carlo
FPGA hardware implementation
Summary Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.
Language eng
DOI 10.1016/j.procs.2014.05.228
Field of Research 010401 Applied Statistics
010406 Stochastic Analysis and Modelling
Socio Economic Objective 920103 Cardiovascular System and Diseases
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution Non-Commercial No-Derivatives licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082248

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.