FPGA implementation of adaptive segmentation for non-stationary biomedical signals
FPGA implementation of adaptive segmentation for non-stationary biomedical signals
- Author(s): B. Jiao ; S. Krishnan ; A. Kabbani
- DOI: 10.1049/iet-cds.2009.0141
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- Author(s): B. Jiao 1 ; S. Krishnan 1 ; A. Kabbani 1
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View affiliations
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Affiliations:
1: Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada
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Affiliations:
1: Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada
- Source:
Volume 4, Issue 3,
May 2010,
p.
239 – 250
DOI: 10.1049/iet-cds.2009.0141 , Print ISSN 1751-858X, Online ISSN 1751-8598
A novel field programmable gate array (FPGA) implementation of adaptive segmentation for non-stationary biomedical signals is presented. The design uses Simulink-to-FPGA methodology and has been successfully implemented onto Xilinx Virtex II Pro device. The implementation is based on the recursive least-squares lattice (RLSL) algorithm using double-precision floating-point arithmetic and is programmable for users providing data length, system order and threshold selection functions. The implemented RLSL design provides very good performance in obtaining accurate conversion factor values with a mean correlation above 99% and detecting segment boundaries with high accuracy for both synthesised and real-world biomedical signals.
Inspec keywords: least squares approximations; field programmable gate arrays; medical signal processing
Other keywords:
Subjects: Signal processing and detection; Biomedical engineering; Logic circuits; Biology and medical computing; Interpolation and function approximation (numerical analysis); Biomedical measurement and imaging; Logic and switching circuits; Digital signal processing; Interpolation and function approximation (numerical analysis); Numerical approximation and analysis
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