Identifying the muscle synergy pattern during human grasping
DOI:
https://doi.org/10.14738/jbemi.16.779Keywords:
Surface EMG, Hals algorithm, muscle synergyAbstract
In this work, a methodology has been proposed and evaluated for identification the muscle synergy patterns during human grasping.The proposed approach is based on decomposition analysis of involved muscle activation profiles utilizing the Hierarchical Alternating Least Squares (HALS) algorithm. The surface EMG signals of Flexor Digital Superfacialis and Flexor Pollicis Longus muscles were recorded during grasping an cylindrical object. EMG signals were full-wave rectified and smoothed through a low pass filter. Then the HALS algorithm was utilized for decomposition of muscle activation profiles. The HALS algorithm can be efficiently used instead of NNMF (non-negative matrix factorization) method. The HALS method not only provides a very good convergence property but also there is not the non-negativity constraint for the decomposed factors. The results of evaluations are interesting and promising.
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