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Masked least-squares averaging in processing of scanning-EMG recordings with multiple discharges

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Abstract

Removing artifacts from nearby motor units is one of the main objectives when processing scanning-EMG recordings. Methods such as median filtering or masked least-squares smoothing (MLSS) can be used to eliminate artifacts in recordings with just one discharge of the motor unit potential (MUP) at each location. However, more effective artifact removal can be achieved if several discharges per position are recorded. In this case, processing usually involves averaging the discharges available at each position and then applying a median filter in the spatial dimension. The main drawback of this approach is that the median filter tends to distort the signal waveform. In this paper, we present a new algorithm that operates on multiple discharges simultaneously and in the spatial dimension. We refer to this algorithm as the multi-masked least-squares smoothing (MMLSS) algorithm: an extension of the MLSS algorithm for the case of multiple discharges. The algorithm is tested using simulated scanning-EMG signals in different recording conditions, i.e., at different levels of muscle contraction and for different numbers of discharges per position. The results demonstrate that the algorithm eliminates artifacts more effectively than any previously available method and does so without distorting the waveform of the signal.

The raw scanning-EMG signal, which can be composed by several discharges of the MU, is processed by the MMLSS algorithm so as to eliminate the artifact interference. Firstly, artifacts are detected for each discharge from the raw signal, obtaining a multi-discharge validity mask that indicates the samples that have been corrupted by artifacts. Secondly, a least-squares smoothing procedure simultaneously operating in the spatial dimension and among the discharges is applied to the raw signal. This second step is performed using only the not contaminated samples according to the validity mask. The resulting MMLSS-processed scanning-EMG signal is clean of artifact interference.

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Funding

This work has been supported by the Spanish Ministry of Science and Innovation under the project PID2019-109062RB-I00.

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Authors and Affiliations

  1. Department of Electrical, Electronic and Communication Engineering, Public University of Navarra, 31006, Navarra, Spain

    Íñigo Corera, Armando Malanda, Javier Rodríguez-Falces & Javier Navallas

  2. Bioengineering Group, IdiSNA (Instituto de Investigación Sanitaria de Navarra), 31008, Navarra, Spain

    Armando Malanda, Javier Rodríguez-Falces & Javier Navallas

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  1. Íñigo Corera
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  2. Armando Malanda
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  3. Javier Rodríguez-Falces
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  4. Javier Navallas
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Correspondence to Íñigo Corera.

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Corera, Í., Malanda, A., Rodríguez-Falces, J. et al. Masked least-squares averaging in processing of scanning-EMG recordings with multiple discharges. Med Biol Eng Comput 58, 3063–3073 (2020). https://doi.org/10.1007/s11517-020-02274-x

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  • DOI: https://doi.org/10.1007/s11517-020-02274-x

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