DocumentCode :
2712348
Title :
Investigating the properties of optimal sensory and motor synergies in a nonlinear model of arm dynamics
Author :
Bayati, Hamidreza ; Vahdat, Shahabeddin ; Vahdat, Bijan Vosoughi
Author_Institution :
Dept. of Electr. Eng., Sharif Univ. of Technol., Kish Island, Iran
fYear :
2009
fDate :
14-19 June 2009
Firstpage :
272
Lastpage :
279
Abstract :
The vertebrate nervous system produces a wide range of movements flexibly and efficiently, in spite of high complexity and nonlinearity of their motor system. The existence of building blocks in motor system known as synergies can be a convincing solution to overcome the computational complexity. In mathematical perspective, optimal feedback control as a theory of motor coordination provides a coherent framework that leads to optimal synergies. Alternatively, some experiments in vertebrates have shown the involvement of spinal motor primitives in movement execution. The goal of this study is first extracting optimal synergies in nonlinear dynamics case and then investigating their biological plausibility according to reported experimental evidences. We investigated the theoretical properties of optimal synergies of reaching tasks in a 2-joint 6-muscle arm model. Our results show that optimal motor synergies have properties similar to the properties of motor primitives.
Keywords :
biomechanics; muscle; neurophysiology; arm dynamics; motor coordination; motor primitives; motor synergy; muscle arm model; nonlinear dynamics; optimal sensory; Biological neural networks; Biological system modeling; Computational complexity; Computational modeling; Cost function; Feedback control; Nervous system; Nonlinear dynamical systems; Stochastic processes; Systems engineering education;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
ISSN :
1098-7576
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2009.5178941
Filename :
5178941
Link To Document :
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