Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware
Bodisco, Timothy A., D'Netto, Jason, Kelson, Neil A., Banks, Jasmine, & Hayward, Ross F. (2014) Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware. Procedia Computer Science, 29, pp. 2442-2448.
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.
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|Item Type:||Journal Article|
|Additional Information:||Selection and peer-review under responsibility of the Scientific Programme Committee of ICCS 2014|
|Keywords:||ECG signal analysis, Markov-chain Monte Carlo, FPGA hardware implementation|
|Subjects:||Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Applied Statistics (010401)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Circuits and Systems (090601)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
|Divisions:||Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Current > QUT Faculties and Divisions > Division of Technology, Information and Library Services
Current > Schools > School of Electrical Engineering & Computer Science
Current > Research Centres > High Performance Computing and Research Support
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2014 The Author(s)|
|Copyright Statement:||This is the author’s version of a work that was accepted for publication in Procedia Computer Science. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Procedia Computer Science, [VOL 29 (2014)] DOI: 10.1016/j.procs.2014.05.228|
|Deposited On:||15 Jun 2014 22:41|
|Last Modified:||12 Aug 2014 19:33|
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