Literature DB >> 18585945

Effect of spatial filtering on crosstalk reduction in surface EMG recordings.

Luca Mesin1, Stuart Smith, Suzanne Hugo, Suretha Viljoen, Tania Hanekom.   

Abstract

Increasing the selectivity of the detection system in surface electromyography (EMG) is beneficial in the collection of information of a specific portion of the investigated muscle and to reduce the contribution of undesired components, such as non-propagating components (due to generation or end-of-fibre effects) or crosstalk from nearby muscles. A comparison of the ability of different spatial filters to reduce the amount of crosstalk in surface EMG measurements was conducted in this paper using simulated signals. It focused on the influence of different properties of the muscle anatomy (changing subcutaneous layer thickness, skin conductivity, fibre length) and detection system (single, double and normal double differential, with two inter-electrode distances - IED) on the amount of crosstalk present in the measurements. A cylindrical multilayer (skin, subcutaneous tissue, muscle, bone) analytical model was used to simulate single fibre action potentials (SFAPs). Fibres were grouped together in motor units (MUs) and motor unit action potentials (MUAPs) were obtained by adding the SFAPs of the corresponding fibres. Interference surface EMG signals were obtained, modelling the recruitment of MUs and rate coding. The average rectified value (ARV) and mean frequency (MNF) content of the EMG signals were studied and used as a basis for determining the selectivity of each spatial filter. From these results it was found that the selectivity of each spatial filter varies depending on the transversal location of the measurement electrodes and on the anatomy. An increase in skin conductivity favourably affects the selectivity of normal double differential filters as does an increase in subcutaneous layer thickness. An increase in IED decreases the selectivity of all the analysed filters.

Mesh:

Year:  2008        PMID: 18585945     DOI: 10.1016/j.medengphy.2008.05.006

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  7 in total

1.  Spatial variability in cortex-muscle coherence investigated with magnetoencephalography and high-density surface electromyography.

Authors:  Harri Piitulainen; Alberto Botter; Mathieu Bourguignon; Veikko Jousmäki; Riitta Hari
Journal:  J Neurophysiol       Date:  2015-09-09       Impact factor: 2.714

2.  Selective activation of the rectus abdominis muscle during low-intensity and fatiguing tasks.

Authors:  Paulo H Marchetti; André F Kohn; Marcos Duarte
Journal:  J Sports Sci Med       Date:  2011-06-01       Impact factor: 2.988

3.  Variability in spatio-temporal pattern of trapezius activity and coordination of hand-arm muscles during a sustained repetitive dynamic task.

Authors:  Afshin Samani; Divya Srinivasan; Svend Erik Mathiassen; Pascal Madeleine
Journal:  Exp Brain Res       Date:  2016-10-14       Impact factor: 1.972

4.  Analysis of Muscle Load-Sharing in Patients With Lateral Epicondylitis During Endurance Isokinetic Contractions Using Non-linear Prediction.

Authors:  Mónica Rojas-Martínez; Joan Francesc Alonso; Mislav Jordanić; Miguel Ángel Mañanas; Joaquim Chaler
Journal:  Front Physiol       Date:  2019-09-24       Impact factor: 4.566

Review 5.  Electrode Size and Placement for Surface EMG Bipolar Detection from the Brachioradialis Muscle: A Scoping Review.

Authors:  Andrea Merlo; Maria Chiara Bò; Isabella Campanini
Journal:  Sensors (Basel)       Date:  2021-11-03       Impact factor: 3.576

6.  Analysis of muscle fiber conduction velocity enables reliable detection of surface EMG crosstalk during detection of nociceptive withdrawal reflexes.

Authors:  Michael Brun Jensen; José Alberto Biurrun Manresa; Ken Steffen Frahm; Ole Kæseler Andersen
Journal:  BMC Neurosci       Date:  2013-03-26       Impact factor: 3.288

7.  Reduce Surface Electromyography Channels for Gesture Recognition by Multitask Sparse Representation and Minimum Redundancy Maximum Relevance.

Authors:  Yali Qu; Haoyan Shang; Jing Li; Shenghua Teng
Journal:  J Healthc Eng       Date:  2021-05-27       Impact factor: 2.682

  7 in total

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