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dc.contributor.authorKian, Azadeh
dc.contributor.authorPizzolato, Claudio
dc.contributor.authorHalaki, Mark
dc.contributor.authorGinn, Karen
dc.contributor.authorLloyd, David
dc.contributor.authorReed, Darren
dc.contributor.authorAckland, David
dc.date.accessioned2021-10-13T03:39:43Z
dc.date.available2021-10-13T03:39:43Z
dc.date.issued2021
dc.identifier.issn0021-9290
dc.identifier.doi10.1016/j.jbiomech.2021.110698
dc.identifier.urihttp://hdl.handle.net/10072/408991
dc.description.abstractCalibration of neuromusculoskeletal models using functional tasks is performed to calculate subject-specific musculotendon parameters, as well as coefficients describing the shape of muscle excitation and activation functions. The objective of the present study was to employ a neuromusculoskeletal model of the shoulder driven entirely from muscle electromyography (EMG) to quantify the influence of different model calibration strategies on muscle and joint force predictions. Three healthy adults performed dynamic shoulder abduction and flexion, followed by calibration tasks that included reaching, head touching as well as active and passive abduction, flexion and axial rotation, and submaximal isometric abduction, flexion and axial rotation contractions. EMG data were simultaneously measured from 16 shoulder muscles using surface and intramuscular electrodes, and joint motion evaluated using video motion analysis. Muscle and joint forces were calculated using subject-specific EMG-driven neuromusculoskeletal models that were uncalibrated and calibrated using (i) all calibration tasks (ii) sagittal plane calibration tasks, and (iii) scapular plane calibration tasks. Joint forces were compared to published instrumented implant data. Calibrating models across all tasks resulted in glenohumeral joint force magnitudes that were more similar to instrumented implant data than those derived from any other model calibration strategy. Muscles that generated greater torque were more sensitive to calibration than those that contributed less. This study demonstrates that extensive model calibration over a broad range of contrasting tasks produces the most accurate and physiologically relevant musculotendon and EMG-to-activation parameters. This study will assist in development and deployment of subject-specific neuromusculoskeletal models.
dc.description.peerreviewedYes
dc.languageeng
dc.publisherElsevier BV
dc.relation.ispartofpagefrom110698
dc.relation.ispartofjournalJournal of Biomechanics
dc.relation.ispartofvolume129
dc.subject.fieldofresearchHuman biophysics
dc.subject.fieldofresearchBiomechanical engineering
dc.subject.fieldofresearchBiomechanics
dc.subject.fieldofresearchBiomedical engineering
dc.subject.fieldofresearchSports science and exercise
dc.subject.fieldofresearchcode320802
dc.subject.fieldofresearchcode400303
dc.subject.fieldofresearchcode420701
dc.subject.fieldofresearchcode4003
dc.subject.fieldofresearchcode4207
dc.subject.keywordsBiomechanical model
dc.subject.keywordsDeltoid
dc.subject.keywordsElectromyography
dc.subject.keywordsRotator cuff
dc.subject.keywordsShoulder
dc.titleThe effectiveness of EMG-driven neuromusculoskeletal model calibration is task dependent
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationKian, A; Pizzolato, C; Halaki, M; Ginn, K; Lloyd, D; Reed, D; Ackland, D, The effectiveness of EMG-driven neuromusculoskeletal model calibration is task dependent, Journal of Biomechanics, 2021, 129, pp. 110698
dcterms.dateAccepted2021-08-12
dc.date.updated2021-10-08T01:32:29Z
gro.hasfulltextNo Full Text
gro.griffith.authorLloyd, David
gro.griffith.authorPizzolato, Claudio


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