Positive Health Online

Abstract

SABZEVARI and COLLEAGUES,    1 Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran; 2 Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; 3 Research Center of Biomedical Technology and Robotics, Tehran University of Medical Sciences, Tehran, Iran; 4 Department of Neurology, Mashhad University of Medical Sciences, Mashhad, Iran.

Background

Muscle synergy is the activation of a group of muscles that contribute to a particular movement. The goal of the present study is to examine the hypothesis that human reaching movements at different speeds share similar muscle synergies and to investigate the kinesiology basis and innervation of muscles.

Methodology

Electromyographic activity from six muscles of the upper limb and shoulder girdle were recorded during three movements at different speeds, i.e. slow, moderate and fast. The effect of window length on the RMS signal of the EMG was analyzed and then EMG envelope signals were decomposed using non-negative matrix factorization. For each of the ten subjects, three synergies were extracted which accounted for at least 99% of the (variance accounted for) VAF . For each movement, the muscle synergies and muscle activation coefficients of all participants were clustered in to three partitions. Investigation showed a high similarity and dependency of cluster members due to the cosine similarity and mutual information in muscle synergy clustering. For further verification, the EMG envelope signals for all subjects were reconstructed.

Results

The results indicated a lower reconstruction error using the center of the muscle synergy clusters in comparison with the average of the activation coefficients, which confirms the current research's hypothesis.

Conclusion

References

Vahid Reza Sabzevari  1 , Amir Homayoun Jafari  2   3 , Reza Boostani  4. Muscle synergy extraction during arm reaching movements at different speeds. Technol Health Care: 25(1):123-136. doi: 10.3233/THC-161256. 2017.