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Research Papers

Validation of an EMG-Driven, Graphically Based Isometric Musculoskeletal Model of the Cervical Spine

[+] Author and Article Information
Kevin J. Netto

School of Exercise and Nutrition Sciences, Deakin University Burwood, Victoria 3125, Australia; School of Exercise, Biomedical and Health Sciences, Edith Cowan University Joondalup, Western Australia 6027, Australiakevin.netto@deakin.edu.au

Angus F. Burnett

School of Exercise, Biomedical and Health Sciences, Edith Cowan University Joondalup, Western Australia 6027, Australiaa.burnett@ecu.edu.au

Jonathon P. Green

 ICON Technologies Pty Ltd., Victoria Park, Western Australia 6979, Australiajg@icon-tech.com.au

Julian P. Rodrigues

Centre for Neuromuscular and Neurological Disorders, University of Western Australia, Nedlands, Western Australia 6009, Australiajrod@cyllene.uwa.edu.au

J Biomech Eng 130(3), 031014 (May 01, 2008) (8 pages) doi:10.1115/1.2913234 History: Received March 26, 2007; Revised March 10, 2008; Published May 01, 2008

EMG-driven musculoskeletal modeling is a method in which loading on the active and passive structures of the cervical spine may be investigated. A model of the cervical spine exists; however, it has yet to be criterion validated. Furthermore, neck muscle morphometry in this model was derived from elderly cadavers, threatening model validity. Therefore, the overall aim of this study was to modify and criterion validate this preexisting graphically based musculoskeletal model of the cervical spine. Five male subjects with no neck pain participated in this study. The study consisted of three parts. First, subject-specific neck muscle morphometry data were derived by using magnetic resonance imaging. Second, EMG drive for the model was generated from both surface (Drive 1: N=5) and surface and deep muscles (Drive 2: N=3). Finally, to criterion validate the modified model, net moments predicted by the model were compared against net moments measured by an isokinetic dynamometer in both maximal and submaximal isometric contractions with the head in the neutral posture, 20deg of flexion, and 35deg of extension. Neck muscle physiological cross sectional area values were greater in this study when compared to previously reported data. Predictions of neck torque by the model were better in flexion (18.2% coefficient of variation (CV)) when compared to extension (28.5% CV) and using indwelling EMG did not enhance model predictions. There were, however, large variations in predictions when all the contractions were compared. It is our belief that further work needs to be done to improve the validity of the modified EMG-driven neck model examined in this study. A number of factors could potentially improve the model with the most promising probably being optimizing various modeling parameters by using methods established by previous researchers investigating other joints of the body.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

Average PCSA values from five subjects obtained from MRI; error bar=1 standard deviation

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Figure 2

Comparison of flexion neck torques measured by the dynamometer and neck torques predicted by the model by using surface EMG as drive; group (N=5) mean and SD data

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Figure 3

Comparisons of extension neck torques measured by the dynamometer and neck torques predicted by the model by using surface EMG only (Drive 1) and a combination of surface and indwelling EMG (Drive 2); group (Drive 1: N=5, Drive 2: N=3) mean and SD data

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