Motor unit territories in juvenile myoclonic epilepsy patients

Goker, Imran; Baslo, Mehmet Barış; Ertaş, Mustafa; Ülgen, Yekta

doi:10.1109/iembs.2009.5334552

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2009

DOI: 10.1109/iembs.2009.5334552

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Motor unit territories in juvenile myoclonic epilepsy patients

Imran Goker

Mehmet Barış Baslo

Mustafa Ertaş

et al.

Abstract: In this study, the scanning EMG technique was implemented to investigate electrophysiological cross-sections of the motor unit (MU) territories in healthy volunteers and in subjects with juvenile myoclonic epilepsy and spinal muscular atrophy. Measurements were taken intramuscularly by means of two concentric needle electrodes from biceps brachialis muscles. 3-D maps of the MU territories were plotted for each MU to determine the lengths of MU cross-section and the maximum amplitudes of each MU. There was evid… Show more

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Cited by 2 publications

References 7 publications

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A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings

Corera

Eciolaza

Rubio

et al. 2018

Med Biol Eng Comput

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Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Although the traditional processing based on the median filtering is effective in removing such interference, it distorts the physiological waveform of the scanning-EMG signal. In this study, we describe a new scanning-EMG signal processing algorithm that preserves the physiological signal waveform while effectively removing interference from other motor units. To obtain a cleaned-up version of the scanning signal, the masked least-squares smoothing (MLSS) algorithm recalculates and replaces each sample value of the signal using a least-squares smoothing in the spatial dimension, taking into account the information of only those samples that are not contaminated with activity of other motor units. The performance of the new algorithm with simulated scanning-EMG signals is studied and compared with the performance of the median algorithm and tested with real scanning signals. Results show that the MLSS algorithm distorts the waveform of the scanning-EMG signal much less than the median algorithm (approximately 3.5 dB gain), being at the same time very effective at removing interference components. Graphical AbstractThe raw scanning-EMG signal (left figure) is processed by the MLSS algorithm in order to remove the artifact interference. Firstly, artifacts are detected from the raw signal, obtaining a validity mask (central figure) that determines the samples that have been contaminated by artifacts. Secondly, a least-squares smoothing procedure in the spatial dimension is applied to the raw signal using the not contaminated samples according to the validity mask. The resulting MLSS-processed scanning-EMG signal (right figure) is clean of artifact interference.

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A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings

Corera

Eciolaza

Rubio

et al. 2018

Med Biol Eng Comput

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

Corera

Malanda

Rodriguez‐Falces

et al. 2020

Med Biol Eng Comput

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Removing artifacts from nearby motor units is one of the main objectives when processing scanning-EMG recordings. Methods such as median filtering or masked leastsquares 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. Results demonstrate that the algorithm eliminates artifacts more effectively than any previously available method and does so without distorting the waveform of the signal.

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Motor unit territories in juvenile myoclonic epilepsy patients

Cited by 2 publications

References 7 publications

A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings

A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings

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

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