Computation of ECG Signal Features Using MCMC Modelling in Software and FPGA Reconfigurable Hardware | Zendy

Timothy A. Bodisco | Zendy; Jason D’Netto | Zendy; Neil A. Kelson | Zendy; Jasmine Banks | Zendy; Ross Hayward | Zendy

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Computation of ECG Signal Features Using MCMC Modelling in Software and FPGA Reconfigurable Hardware

Author(s) -

Timothy A. Bodisco,

Jason D’Netto,

Neil A. Kelson,

Jasmine Banks,

Ross Hayward

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.05.228

Subject(s) - computer science , markov chain monte carlo , computation , field programmable gate array , software , signal (programming language) , heart beat , software implementation , dependency (uml) , computer hardware , computational science , embedded system , algorithm , computer engineering , real time computing , artificial intelligence , bayesian probability , operating system , medicine , programming language

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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