Influence of Fibres Inclination on the Degree of Gaussianity of Simulated Surface EMG Signals

dc.contributor.authorMessaoudi, Noureddine
dc.contributor.authorBekka, Raïs El’hadi
dc.contributor.authorBelkacem, Samia
dc.date.accessioned2020-12-16T10:57:11Z
dc.date.available2020-12-16T10:57:11Z
dc.date.issued2020
dc.description.abstractThe main purpose of this simulation study was to estimate the effect of muscle fibres inclination on the degree of Gaussianity of the surface electromyographic (sEMG) signals generated in a cylindrical multilayer volume conductor constituted by bone, muscle, fat and skin layers and detected by the longitudinal single differential (LSD), inverse binomial of order two (IB2), maximum kurtosis filter (MKF) and three rings (3RGs) systems. This estimation was based on the computation of the Kurtosis of simulated sEMG signals when the fibres inclination angle (FIA) varied from 0° to 180° in a step of 2.5°. For each FIA, the effects of the motor units (MUs) recruitment range (RR) and the level of muscular voluntary contraction (MVC) were also assessed. The results showed that with the same detection system, the degree of Gaussianity of the EMG signal is highly influenced by the fibres inclination with respect to the electrodes arrangement. Indeed, the classification of the studied detection systems according to the degree of Gaussianity of sEMG signals detected by them is different from a FIA interval to another i.e. a surface EMG signal detected by any detection system may be the most Gaussian with an FIA interval as it may be the least Gaussian in another FIA interval.en_US
dc.description.sponsorshipIn-Cooperation: NWPU, Universidade Nova de Lisboaen_US
dc.identifier.isbn978-1-4503-7571-9
dc.identifier.urihttps://doi.org/10.1145/3405758.3405781
dc.identifier.urihttps://dspace.univ-boumerdes.dz/handle/123456789/5933
dc.language.isoenen_US
dc.publisherACM DIGITAL LIBRARAYen_US
dc.relation.ispartofseriesICBBT 2020: Proceedings of the 2020 12th International Conference on Bioinformatics and Biomedical TechnologyMay 2020;Pages 139–144
dc.relation.ispartofseriesICPS PROCEEDINGS;
dc.subjectComputing methodologiesen_US
dc.subjectModeling and simulationen_US
dc.subjectSimulation evaluationen_US
dc.titleInfluence of Fibres Inclination on the Degree of Gaussianity of Simulated Surface EMG Signalsen_US
dc.typeWorking Paperen_US

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