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Optimization and Implementation of the Wavelet Based Algorithms for Embedded Biomedical Signal Processing
Computer Science and Information Systems, Tome 10 (2013) no. 1 Cet article a éte moissonné depuis la source Computer Science and Information Systems website

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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.
Keywords: wavelet transform, microcontroller, QRS, denoising 
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     author = {Radovan Stojanovi\'c and Sa\v{s}a Kne\v{z}evi\'c and Dejan Karadagli\'c and Goran Deved\v{z}i\'c},
     title = {Optimization and {Implementation} of the {Wavelet} {Based} {Algorithms} for {Embedded} {Biomedical} {Signal} {Processing}},
     journal = {Computer Science and Information Systems},
     year = {2013},
     volume = {10},
     number = {1},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2013_10_1_a23/}
}
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Radovan Stojanović; Saša Knežević; Dejan Karadaglić; Goran Devedžić. Optimization and Implementation of the Wavelet Based Algorithms for Embedded Biomedical Signal Processing. Computer Science and Information Systems, Tome 10 (2013) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2013_10_1_a23/