Consequences of biomechanically constrained tasks in the design 1 and interpretation of synergy analyses
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چکیده
Authors and affiliations: 5 1,2,* Katherine M. Steele, 2,3,4 Matthew C. Tresch, and 2,3,4 Eric J. Perreault 6 7 1 Mechanical Engineering, University of Washington, Seattle, WA, USA 8 2 Sensorimotor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USA 9 3 Biomedical Engineering, Northwestern University, Evanston, IL, USA 10 4 Physical Medicine & Rehabilitation, Northwestern University Feinberg School of Medicine, 11 Chicago, IL, USA 12 13 14 Correspondence: 15 Katherine M. Steele 16 Mechanical Engineering 17 University of Washington 18 Stevens Way, Box 352600 19 Seattle, WA, USA 98195 20 [email protected] 21 206-685-2390 22 23 Running title: Accuracy of synergies from decomposition algorithms 24 25 Revision submitted to: Journal of Neurophysiology 26 Revision 2: 12/19/2014 27 Revision: 9/22/2014 28 Original: 10/28/2013 29 30 Word Count: 6,443 31 Articles in PresS. J Neurophysiol (January 14, 2015). doi:10.1152/jn.00769.2013
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Consequences of biomechanically constrained tasks in the design and interpretation of synergy analyses.
Matrix factorization algorithms are commonly used to analyze muscle activity and provide insight into neuromuscular control. These algorithms identify low-dimensional subspaces, commonly referred to as synergies, which can describe variation in muscle activity during a task. Synergies are often interpreted as reflecting underlying neural control; however, it is unclear how these analyses are in...
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