Optimization and Implementation of the Wavelet Based Algorithms for Embedded Biomedical Signal Processing
- University of Montenegro, Faculty of Electrical Engineering
Montenegro
stox@ac.me, sasaknezevic@live.com - Glasgow Caledonian University, School of Engineering and Built Environment
UK
Dejan.Karadaglic@gcu.ac.uk - University of Kragujevac, Faculty of Engineering
Serbia
devedzic@kg.ac.rs
Abstract
Existing biomedical wavelet based applications exceed the computational, memory and consumption resources of low-complexity embedded systems. In order to make such systems capable to use wavelet transforms, optimization and implementation techniques are proposed. The Real Time QRS Detector and “De-noising” Filter are developed and implemented in 16-bit fixed point microcontroller achieving 800 Hz sampling rate, occupation of less than 500 bytes of data memory, 99.06% detection accuracy, and 1 mW power consumption. By evaluation of the obtained results it is found that the proposed techniques render negligible degradation in detection accuracy of -0.41% and SNR of -2.8%, behind 2-4 times faster calculation, 2 times less memory usage and 5% energy saving. The same approach can be applied with other signals where the embedded implementation of wavelets can be beneficial.
Key words
wavelet transform, microcontroller, QRS, denoising
Digital Object Identifier (DOI)
https://doi.org/10.2298/CSIS120517013S
Publication information
Volume 10, Issue 1 (Januar 2013)
Year of Publication: 2013
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium
Full text
Available in PDF
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How to cite
Stojanović, R., Knežević, S., Karadaglić, D., Devedžić, G.: Optimization and Implementation of the Wavelet Based Algorithms for Embedded Biomedical Signal Processing. Computer Science and Information Systems, Vol. 10, No. 1, 503-523. (2013), https://doi.org/10.2298/CSIS120517013S