Adaptive algorithms for real-time filtering of electrocardiogram with multilevel noise estimation

Published: 28 Jan 2020 | Version 1 | DOI: 10.17632/jxdynf3g6x.1
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Description of this data

The computer programs implement the adaptive algorithms for ECG signal filtering and numerical simulation for evaluation of filter effectiveness. The adaptive algorithms with use Hampel identifiers is an author’s development.
To launch a program, enter the name of the program and the ECG model signal in the command line. For example: ahm2rt.exe clean.txt. The test signal parameters and parameters of the filtering algorithms are read from the text file named as “filters.txt”. The program requests the additive and multiplicative noise variance, the probability and the amplitude of the isolated spikes, and the number of realizations for statistical averaging of the calculated filter performance indicators. For example, via the “space” key enter: 0.0001 0 0 0 200, then press “Enter”. To apply filtering to a test signal which is read from a text file, select the menu item "Load from file" by pressing the key "6". The filter results are put in the “RESULT” subfolder. The filter efficiency estimates are written to the "MSE.res" and "SNR.res" output text files. The input signal has an extension “.x” (no noise), “.xn” (with simulated noise), “.xns” (with noise and spikes). The signals from filter algorithms outputs have the extension “.yf”. Also, files with functions of identifiers used to adapt the algorithm parameters to the local signal behavior and to the changes in the noise level and with adaptable filter parameters, and other intermediate signals are put to the “RESULT” subfolder.
The program was compiled by Free Pascal.

Experiment data files

Latest version

  • Version 1

    2020-01-28

    Published: 2020-01-28

    DOI: 10.17632/jxdynf3g6x.1

    Cite this dataset

    Tulyakova, Nataliya (2020), “Adaptive algorithms for real-time filtering of electrocardiogram with multilevel noise estimation ”, Mendeley Data, v1 http://dx.doi.org/10.17632/jxdynf3g6x.1

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Digital Signal Processing Algorithm

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