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Onset detection in surface electromyographic signals across isometric explosive and ramped contractions: a comparison of computer-based methods

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dc.contributor.author Crotty, Evan D.
dc.contributor.author Furlong, Laura-Anne M.
dc.contributor.author Hayes, Kevin
dc.contributor.author Harrison, Andrew J.
dc.date.accessioned 2021-05-14T13:15:58Z
dc.date.available 2021-05-14T13:15:58Z
dc.date.issued 2021
dc.identifier.uri http://hdl.handle.net/10344/10080
dc.description peer-reviewed en_US
dc.description.abstract Objective. Accurate identification of surface electromyography (EMG) muscle onset is vital when examining short temporal parameters such as electromechanical delay. The visual method is considered the ‘gold standard’ in onset detection. Automatic detection methods are commonly employed to increase objectivity and reduce analysis time, but it is unclear if they are sensitive enough to accurately detect EMG onset when relating them to short-duration motor events. Approach. This study aimed to determine: (1)if automatic detection methods could be used interchangeably with visual methods in detecting EMG onsets(2)if the Teager–Kaiser energy operator(TKEO) as a conditioning step would improve the accuracy of popular EMG onset detection methods. The accuracy of three automatic onset detection methods: approximated generalized likelihood ratio (AGLR), TKEO, and threshold-based method were examined against the visual method. EMG signals from fast, explosive, and slow, ramped isometric plantarflexor contractions were evaluated using each technique. Main results. For fast, explosive contractions, the TKEO was the best-performing automatic detection method, with a low bias level(4.7 ± 5.6 ms) and excellent intraclass correlation coefficient (ICC) of 0.993, however with wide limits of agreement (LoA) (−6.2 to +15.7 ms). For slow, ramped contractions, the AGLR with TKEO conditioning was the best-performing automatic detection method with the smallest bias(11.3 ± 32.9 ms) and excellent ICC(0.983) but produced wide LoA (−53.2 to +75.8 ms). For visual detection, the inclusion of TKEO conditioning improved inter-rater and intra-rater reliability across contraction types compared with visual detection without TKEO conditioning. Significance. In conclusion, the examined automatic detection methods are not sensitive enough to be applied when relating EMG onset to a motor event of short duration. To attain the accuracy needed, visual detection is recommended. The inclusion of TKEO as a conditioning step before visual detection of EMG onsets is recommended to improve visual detection reliability. en_US
dc.language.iso eng en_US
dc.publisher IOP Publishing en_US
dc.relation.ispartofseries Physiological Measurement;42, 035010
dc.relation.uri https://doi.org/10.1088/1361-6579/abef56
dc.subject electromyography en_US
dc.subject muscle onset en_US
dc.subject Teager–Kaiser energy operator en_US
dc.subject signal processing en_US
dc.title Onset detection in surface electromyographic signals across isometric explosive and ramped contractions: a comparison of computer-based methods en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1088/1361-6579/abef56
dc.contributor.sponsor IRC en_US
dc.relation.projectid GOIPG/2017/378 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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