A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings.
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. Alth...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 8; pp. 1391 - 1403 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=130773115&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 130773115 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Aug2018 vid: 56 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 130773115 130773115 NLM29327334 130773115 10.1007/s11517-017-1773-0 NLM29327334 130773115 ppf: 1391 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings. aug: au: Corera, Íñigo Eciolaza, Adrián Rubio, Oliver Malanda, Armando Rodríguez-Falces, Javier Navallas, Javier affil: Department of Electrical and Electronic Engineering, Public University of Navarra, 31006, Navarra, Spain sug: subj: Electromyography Artifacts Algorithms Signal Processing, Computer Assisted Action Potentials Computer Simulation Muscle Contraction Physiology Regression Human Funding Source ab: 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 Abstract The 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. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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