Document Type : Full Research Paper


1 M.Sc., Bioelectric Group, Bioengineering School, Amirkabir University of Technology

2 Professor, Bioelectric Group, Bioengineering School, Amirkabir University of Technology

3 Associate professor, Bioelectric Group, Bioengineering School, Amirkabir University of Technology



The central nervous system (CNS) uses a redundant set of joints and muscles to ensure both flexible and stable movements. How the CNS faces the complexity of control problem is not still clear. Modular control is one of the most attractive hypotheses in motor control. In this hypothesis, some motor primitives (e.g. muscle synergies) are considered as the building blocks that can be combined to present a vast repertoire of movements. EMG signals are required for extracting muscle synergies and NMF (nonnegative matrix factorization) is one of the most accepted methods for extracting synergies. Due to tonic component elimination of EMG signals involved in reaching movements in vertical planes, the standard NMF method is not applicable to extract muscle synergies. In this paper a modified NMF method, so-called semi-NMF, is applied to resolve the tonic component problem. On the other hand, to improve the accuracy of synergies' estimation and to find the global optimum for the optimization problem, we have proposed using HALS method. The proposed algorithm was applied to the experimental EMG recorded in arm reaching movement in the frontal plane. The results showed a good improvement both in accuracy and repeatability of extracted synergies. In addition, extracted muscle synergies were physiologically interpretable.


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