dc.contributor.author | Ládrová, Martina | |
dc.contributor.author | Martinek, Radek | |
dc.contributor.author | Nedoma, Jan | |
dc.contributor.author | Fajkus, Marcel | |
dc.date.accessioned | 2019-03-12T09:36:09Z | |
dc.date.available | 2019-03-12T09:36:09Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Journal of Biomimetics Biomaterials and Biomedical Engineering. 2019, vol. 40, p. 64-70. | cs |
dc.identifier.issn | 2296-9837 | |
dc.identifier.issn | 2296-9845 | |
dc.identifier.uri | http://hdl.handle.net/10084/134190 | |
dc.description.abstract | Electromyogram (EMG) recordings are often corrupted by the wide range of artifacts, which one of them is power line interference (PLI). The study focuses on some of the well-known signal processing approaches used to eliminate or attenuate PLI from EMG signal. The results are compared using signal-to-noise ratio (SNR), correlation coefficients and Bland-Altman analysis for each tested method: notch filter, adaptive noise canceller (ANC) and wavelet transform (WT). Thus, the power of the remaining noise and shape of the output signal are analysed. The results show that the ANC method gives the best output SNR and lowest shape distortion compared to the other methods. | cs |
dc.language.iso | en | cs |
dc.publisher | Trans Tech Publications | cs |
dc.relation.ispartofseries | Journal of Biomimetics Biomaterials and Biomedical Engineering | cs |
dc.relation.uri | http://doi.org/10.4028/www.scientific.net/JBBBE.40.64 | cs |
dc.rights | © 2019 Trans Tech Publications, Switzerland | cs |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | electromyography | cs |
dc.subject | biological signal processing | cs |
dc.subject | power line | cs |
dc.subject | notch filter | cs |
dc.subject | adaptive noise canceller | cs |
dc.subject | wavelet transform | cs |
dc.title | Methods of power line interference elimination in EMG signals | cs |
dc.type | article | cs |
dc.identifier.doi | 10.4028/www.scientific.net/JBBBE.40.64 | |
dc.rights.access | openAccess | |
dc.type.version | publishedVersion | |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.description.volume | 40 | cs |
dc.description.lastpage | 70 | cs |
dc.description.firstpage | 64 | cs |
dc.identifier.wos | 000459402200006 | |