Kargo WJ, Giszter SF (2000) Rapid correction of aimed movements by summation of force-field primitives. Singh KIRE, White G, Edgar T, Hutchinson TE (2018) A systematic review on muscle synergies: from building blocks of motor behavior to a neurorehabilitation tool. Neurorehabilit Neural Repair 29(6):509–516 Harmsen WJ, Bussmann JB, Selles RW, Hurkmans HL, Ribbers GM (2014) A mirror therapy-based action observation protocol to improve motor learning after stroke. Grillner S, Wallen P (1985) Central pattern generators for locomotion, with special reference to vertebrates. Neurophysiolog 103:844–857ĭ’Avella A, Saltiel P, Bizzi E (2003) Combinations of muscle synergies in the construction of a natural motor behavior. Proc Natl Acad Sci USA 106:19563–19568Ĭlark DJ, Ting LH, Zajac FE, Neptune RR, Kautz SA (2010) Merging of healthy motor modules predicts reduced locomotor performance and muscle coordination complexity post-stroke. University of British ColumbiaĬheung VCK, Piron L, Agostini M, Silvoni S, Turolla A, Bizzi E (2009b) Stability of muscle synergies for voluntary actions after cortical stroke in humans. J Neurosci 30(9):3432–3437Ĭhen X (2014) Multimodal biomedical signal processing for corticomuscular coupling analysis. Brain Res Rev 57(1):125–133īradberry TJ, Gentili RJ, Contreras-Vidal JL (2010) Reconstructing Three-Dimensional Hand Movements from Noninvasive Electroencephalographic Signals. J Neurosci 34:13811–13818īizzi E, Cheung V, d’Avella A, Saltiel P, Tresch M (2008) Combining modules for movement. Our results confirm that use of the expression of muscle synergies in brain activity can estimate the neural decoding performance for motor control that can be used to develop neurorehabilitation tools such as neuroprosthesis.Īsavasopon MRS, Kirages DJ et al (2014) Cortical activation associated with muscle synergies of the human male pelvic floor. To compare with the existing methods, our results showed significantly more accuracy of the model performance. Furthermore, the similarity between actual and reconstructed muscle activations was achieved more than 92% for correlation coefficient. The performance of proposed method was evaluated with tenfold cross-validation and muscle synergy estimation of brain activity with R, VAF, and MSE of 84 ± 2.6%, 70 ± 4.7%, and 0.00011 ± 0.00002 were quantified respectively. The Elman neural network was used to decode the relationship between extracted motor commands and muscle synergies. To extract the maximum correlation of neural commands with muscle synergies, application of a combined partial least squares and canonical correlation analysis (PLS-CCA) method was proposed. ![]() To find the relationship between brain activities and muscle synergies, electroencephalogram (EEG) and electromyogram (EMG) signals were acquired simultaneously during activities of daily living. The main purpose of this paper is to develop synergy-based neural decoding of motor primitives, so for the first time, brain activity and muscle synergy map of the upper extremity was investigated in the activity of daily living movements. ![]() Muscle synergies have been hypothesized as specific predefined motor primitives that the central nervous system can reduce the complexity of motor control by using them, but how these are expressed in brain activity is ambiguous yet.
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