Predicted vs. measured paraspinal muscle activity in adolescent idiopathic scoliosis patients: EMG validation of optimization-based musculoskeletal simulations.

Rauber, Cedric; Lüscher, Dominique; Poux, Lucile; Schori, Maria; Deml, Moritz C; Hasler, Carol-Claudius; Bassani, Tito; Galbusera, Fabio; Büchler, Philippe; Schmid, Stefan (2024). Predicted vs. measured paraspinal muscle activity in adolescent idiopathic scoliosis patients: EMG validation of optimization-based musculoskeletal simulations. Journal of biomechanics, 163, p. 111922. Elsevier 10.1016/j.jbiomech.2023.111922

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Musculoskeletal (MSK) models offer great potential for predicting the muscle forces required to inform more detailed simulations of vertebral endplate loading in adolescent idiopathic scoliosis (AIS). In this work, simulations based on static optimization were compared with in vivo measurements in two AIS patients to determine whether computational approaches alone are sufficient for accurate prediction of paraspinal muscle activity during functional activities. We used biplanar radiographs and marker-based motion capture, ground reaction force, and electromyography (EMG) data from two patients with mild and moderate thoracolumbar AIS (Cobb angles: 21° and 45°, respectively) during standing while holding two weights in front (reference position), walking, running, and object lifting. Using a fully automated approach, 3D spinal shape was extracted from the radiographs. Geometrically personalized OpenSim-based MSK models were created by deforming the spine of pre-scaled full-body models of children/adolescents. Simulations were performed using an experimentally controlled backward approach. Differences between model predictions and EMG measurements of paraspinal muscle activity (both expressed as a percentage of the reference position values) at three different locations around the scoliotic main curve were quantified by root mean square error (RMSE) and cross-correlation (XCorr). Predicted and measured muscle activity correlated best for mild AIS during object lifting (XCorr's ≥ 0.97), with relatively low RMSE values. For moderate AIS as well as the walking and running activities, agreement was lower, with XCorr reaching values of 0.51 and comparably high RMSE values. This study demonstrates that static optimization alone seems not appropriate for predicting muscle activity in AIS patients, particularly in those with more than mild deformations as well as when performing upright activities such as walking and running.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Computational Bioengineering
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Musculoskeletal Biomechanics
04 Faculty of Medicine > Department of Orthopaedic, Plastic and Hand Surgery (DOPH) > Clinic of Orthopaedic Surgery
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research

UniBE Contributor:

Rauber, Cedric Simon Pascal, Lüscher, Dominique Sarah, Deml, Moritz Caspar, Büchler, Philippe

Subjects:

600 Technology > 610 Medicine & health
500 Science > 570 Life sciences; biology

ISSN:

1873-2380

Publisher:

Elsevier

Language:

English

Submitter:

Pubmed Import

Date Deposited:

15 Jan 2024 15:19

Last Modified:

10 Feb 2024 00:16

Publisher DOI:

10.1016/j.jbiomech.2023.111922

PubMed ID:

38220500

Uncontrolled Keywords:

AIS Electromyography Motion capture Spine Static optimization

BORIS DOI:

10.48350/191626

URI:

https://boris.unibe.ch/id/eprint/191626

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