Literature DB >> 15320462

Reducing power line interference in digitised electromyogram recordings by spectrum interpolation.

D T Mewett1, K J Reynolds, H Nazeran.   

Abstract

Interference from power lines (50 or 60 Hz) is the largest source of extraneous noise in many bio-electric signals and is within the bandwidth of many such signals. In this study, two different methods were compared for their efficacy in removing 50 Hz noise added to surface electromyogram (EMG) signals free of power line interference. The first was a simple second-order recursive digital notch filter. The second was an approach called spectrum interpolation, in which it is assumed that the magnitude of the original 50 Hz component of the EMG signal can be approximated by interpolation of the amplitude spectrum of the signal. When the spectrum was based on records containing an integer number of cycles of 50 Hz interference, and the frequency resolution was finer than 1 Hz, spectrum interpolation performed similarly to, or significantly better than, the notch filter (p < 0.01). It was also possible to make spectrum interpolation more robust than the notch filter. The Pearson squared correlation coefficient r2 between clean signals and signals processed using the notch filter was reduced from 0.98 to 0.65 when the interference frequency was increased by 0.5 Hz, but r2 for spectrum interpolation at 0.2 Hz resolution was only reduced from 0.99 to 0.85 if spectral values between approximately 49.5 and 50.5 Hz were modified by interpolation.

Mesh:

Year:  2004        PMID: 15320462     DOI: 10.1007/bf02350994

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  11 in total

1.  Detection of hidden rhythms in surface EMG signals with a non-linear time-series tool.

Authors:  G Filligoi; F Felici
Journal:  Med Eng Phys       Date:  1999 Jul-Sep       Impact factor: 2.242

2.  Estimation of surface electromyogram spectral alteration using reduced-order autoregressive model.

Authors:  S Karlsson; J Yu
Journal:  Med Biol Eng Comput       Date:  2000-09       Impact factor: 2.602

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Authors:  H K Bhullar; G H Loudon; J C Fothergill; N B Jones
Journal:  Med Biol Eng Comput       Date:  1990-11       Impact factor: 2.602

4.  Methods to reduce the variability of EMG power spectrum estimates.

Authors:  R V Baratta; M Solomonow; B H Zhou; M Zhu
Journal:  J Electromyogr Kinesiol       Date:  1998-10       Impact factor: 2.368

5.  Accuracy of 50 Hz interference subtraction from an electrocardiogram.

Authors:  I A Dotsinsky; I K Daskalov
Journal:  Med Biol Eng Comput       Date:  1996-11       Impact factor: 2.602

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Authors:  Y Z Ider; H Köymen
Journal:  IEEE Trans Biomed Eng       Date:  1990-06       Impact factor: 4.538

7.  60-HZ interference in electrocardiography.

Authors:  J C Huhta; J G Webster
Journal:  IEEE Trans Biomed Eng       Date:  1973-03       Impact factor: 4.538

8.  Influence of isometric loading on biceps EMG dynamics as assessed by linear and nonlinear tools.

Authors:  C L Webber; M A Schmidt; J M Walsh
Journal:  J Appl Physiol (1985)       Date:  1995-03

9.  Spectral analysis of erector spinae EMG during intermittent isometric fatiguing exercise.

Authors:  J H van Dieën; H M Toussaint; C Thissen; A van de Ven
Journal:  Ergonomics       Date:  1993-04       Impact factor: 2.778

10.  Digital filters for real-time ECG signal processing using microprocessors.

Authors:  M L Ahlstrom; W J Tompkins
Journal:  IEEE Trans Biomed Eng       Date:  1985-09       Impact factor: 4.538

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  15 in total

1.  Outlier detection in high-density surface electromyographic signals.

Authors:  Hamid R Marateb; Monica Rojas-Martínez; Marjan Mansourian; Roberto Merletti; Miguel A Mañanas Villanueva
Journal:  Med Biol Eng Comput       Date:  2011-06-23       Impact factor: 2.602

2.  Location of Reference Electrode Does Not Interfere on Electromyographic Parameters in the Domains of Time and Frequency.

Authors:  Rinaldo Roberto de Jesus Guirro; Alcimar Barbosa Soares; Amanda Caldeira Guirro; Camila Simieli; Alessandra Vairo Peres Boratino; Gabriela de Carvalho; Aline Gobbi; Elaine Caldeira de Oliveira Guirro
Journal:  J Med Syst       Date:  2018-08-11       Impact factor: 4.460

3.  A cepstrum analysis-based classification method for hand movement surface EMG signals.

Authors:  Erdem Yavuz; Can Eyupoglu
Journal:  Med Biol Eng Comput       Date:  2019-08-07       Impact factor: 2.602

4.  Multiscale entropy-based approach to automated surface EMG classification of neuromuscular disorders.

Authors:  Rok Istenic; Prodromos A Kaplanis; Constantinos S Pattichis; Damjan Zazula
Journal:  Med Biol Eng Comput       Date:  2010-05-21       Impact factor: 2.602

5.  Nonlinear parameters of surface EMG in schizophrenia patients depend on kind of antipsychotic therapy.

Authors:  Alexander Yu Meigal; German G Miroshnichenko; Anna P Kuzmina; Saara M Rissanen; Stefanos D Georgiadis; Pasi A Karjalainen
Journal:  Front Physiol       Date:  2015-07-10       Impact factor: 4.566

6.  Reducing power line noise in EEG and MEG data via spectrum interpolation.

Authors:  Sabine Leske; Sarang S Dalal
Journal:  Neuroimage       Date:  2019-01-11       Impact factor: 6.556

7.  The effects of notch filtering on electrically evoked myoelectric signals and associated motor unit index estimates.

Authors:  Xiaoyan Li; William Z Rymer; Guanglin Li; Ping Zhou
Journal:  J Neuroeng Rehabil       Date:  2011-11-23       Impact factor: 4.262

8.  Analysis of linear electrode array EMG for assessment of hemiparetic biceps brachii muscles.

Authors:  Bo Yao; Xu Zhang; Sheng Li; Xiaoyan Li; Xiang Chen; Cliff S Klein; Ping Zhou
Journal:  Front Hum Neurosci       Date:  2015-10-23       Impact factor: 3.169

9.  Quantifying forearm muscle activity during wrist and finger movements by means of multi-channel electromyography.

Authors:  Marco Gazzoni; Nicolò Celadon; Davide Mastrapasqua; Marco Paleari; Valentina Margaria; Paolo Ariano
Journal:  PLoS One       Date:  2014-10-07       Impact factor: 3.240

10.  The influence of common component on myoelectric pattern recognition.

Authors:  Bo Yao; Yun Peng; Xu Zhang; Yingchun Zhang; Ping Zhou; Jiangbo Pu
Journal:  J Int Med Res       Date:  2020-03       Impact factor: 1.671

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