Optimization and Implementation of the Wavelet Based Algorithms for Embedded Biomedical Signal Processing

Radovan Stojanović1, Saša Knežević1, Dejan Karadaglić2 and Goran Devedžić3

  1. University of Montenegro, Faculty of Electrical Engineering
    stox@ac.me, sasaknezevic@live.com
  2. Glasgow Caledonian University, School of Engineering and Built Environment
  3. University of Kragujevac, Faculty of Engineering


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)


Publication information

Volume 10, Issue 1 (Januar 2013)
Year of Publication: 2013
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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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