Zastosowanie uśredniania wielkości sinusoidalnych metodą najmniejszych kwadratów w algorytmach sterowania i redukcji zakłóceń

Chudzik, P.; Tatar, K.; Lisowski, Grzegorz; Kowalski, M.

doi:10.15199/48.2016.05.26

Cited by 1 publication

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“…Nowadays, research and extensive efforts have been made in developing better algorithms, upgrading existing methodologies, 2 of 15 improving detection techniques to reduce noise, and improving EMG signal registration accuracy [4,5]. Thus, many researchers have used different types of advanced methodologies, including Least Mean Square (LMS) filtering [6], wavelet transform, Wigner-Ville distribution, independent component analysis, empirical mode decomposition and higher-order statistics, for analyzing the EMG signal appropriately [7][8][9]. Frequency analysis is widely used for processing biomedical signals in various applications.…”

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confidence: 99%

Processing of EMG Signals with High Impact of Power Line and Cardiac Interferences

et al. 2021

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This work deals with electromyography (EMG) signal processing for the diagnosis and therapy of different muscles. Because the correct muscle activity measurement of strongly noised EMG signals is the major hurdle in medical applications, a raw measured EMG signal should be cleaned of different factors like power network interference and ECG heartbeat. Unfortunately, there are no completed studies showing full multistage signal processing of EMG recordings. In this article, the authors propose an original algorithm to perform muscle activity measurements based on raw measurements. The effectiveness of the proposed algorithm for EMG signal measurement was validated by a portable EMG system developed as a part of the EU research project and EMG raw measurement sets. Examples of removing the parasitic interferences are presented for each stage of signal processing. Finally, it is shown that the proposed processing of EMG signals enables cleaning of the EMG signal with minimal loss of the diagnostic content.

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