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Isometric force generation and kinematic reaching in the upper extremity has been found to be represented by a limited number of muscle synergies, even across task-specific variations. However, the extent of the generalizability of muscle synergies between these two motor tasks within the arm workspace remains unknown. In this study, we recorded electromyographic (EMG) signals from 13 different arm, shoulder, and back muscles of ten healthy individuals while they performed isometric and kinematic center-out target matches to one of 12 equidistant directional targets in the horizontal plane and at each of four starting arm positions. Non-negative matrix factorization was applied to the EMG data to identify the muscle synergies. Five and six muscle synergies were found to represent the isometric force generation and point-to-point reaches. We also found that the number and composition of muscle synergies were conserved across the arm workspace per motor task. Similar tuning directions of muscle synergy activation profiles were observed at different starting arm locations. Between the isometric and kinematic motor tasks, we found that two to four out of five muscle synergies were common in the composition and activation profiles across the starting arm locations. The greater number of muscle synergies that were involved in achieving a target match in the reaching task compared to the isometric task may explain the complexity of neuromotor control in arm reaching movements. Overall, our results may provide further insight into the neuromotor compartmentalization of shared muscle synergies between two different arm motor tasks and can be utilized to assess motor disabilities in individuals with upper limb motor impairments.
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Data Fusion-Based Musculoskeletal Synergies in the Grasping Hand
The hypothesis that the central nervous system (CNS) makes use of synergies or movement primitives in achieving simple to complex movements has inspired the investigation of different types of synergies. Kinematic and muscle synergies have been extensively studied in the literature, but only a few studies have compared and combined both types of synergies during the control and coordination of the human hand. In this paper, synergies were extracted first independently (called kinematic and muscle synergies) and then combined through data fusion (called musculoskeletal synergies) from 26 activities of daily living in 22 individuals using principal component analysis (PCA) and independent component analysis (ICA). By a weighted linear combination of musculoskeletal synergies, the recorded kinematics and the recorded muscle activities were reconstructed. The performances of musculoskeletal synergies in reconstructing the movements were compared to the synergies reported previously in the literature by us and others. The results indicate that the musculoskeletal synergies performed better than the synergies extracted without fusion. We attribute this improvement in performance to the musculoskeletal synergies that were generated on the basis of the cross-information between muscle and kinematic activities. Moreover, the synergies extracted using ICA performed better than the synergies extracted using PCA. These musculoskeletal synergies can possibly improve the capabilities of the current methodologies used to control high dimensional prosthetics and exoskeletons.
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- Award ID(s):
- 2042203
- PAR ID:
- 10406402
- Date Published:
- Journal Name:
- Sensors
- Volume:
- 22
- Issue:
- 19
- ISSN:
- 1424-8220
- Page Range / eLocation ID:
- 7417
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Brain-machine interfaces (BMIs) have become increasingly popular in restoring the lost motor function in individuals with disabilities. Several research studies suggest that the CNS may employ synergies or movement primitives to reduce the complexity of control rather than controlling each DoF independently, and the synergies can be used as an optimal control mechanism by the CNS in simplifying and achieving complex movements. Our group has previously demonstrated neural decoding of synergy-based hand movements and used synergies effectively in driving hand exoskeletons. In this study, ten healthy right-handed participants were asked to perform six types of hand grasps representative of the activities of daily living while their neural activities were recorded using electroencephalography (EEG). From half of the participants, hand kinematic synergies were derived, and a neural decoder was developed, based on the correlation between hand synergies and corresponding cortical activity, using multivariate linear regression. Using the synergies and the neural decoder derived from the first half of the participants and only cortical activities from the remaining half of the participants, their hand kinematics were reconstructed with an average accuracy above 70%. Potential applications of synergy-based BMIs for controlling assistive devices in individuals with upper limb motor deficits, implications of the results in individuals with stroke and the limitations of the study were discussed.more » « less
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Latash, Mark L. (Ed.)This chapter reviews major principles of neural control of movement proposed by N. A. Bernstein based on his biomechanical studies of human movements and published in his 1947 book ‘On Construction of Movements’. These principles include the hierarchical organization of the motor control system; synergistic sensorimotor control; the principle of sensory corrections, and the principles of repetition without repetition and fixating and subsequent releasing kinematic degrees of freedom during motor skill acquisition. These principles simplify control of the musculoskeletal system with redundant degrees of freedom and unpredictable effects of reactive and muscle forces arising in multi-segment kinematic chains. We also discuss the relevant contemporary research that has been inspired by and further developed Bernstein’s ideas. We demonstrate, in particular, examples of complex muscle and kinematic synergies organized by different levels of the motor control system, consequences of loss of proprioceptive sensory corrections on movement coordination, and emergence of economical and stable kinematic and muscle invariant movement characteristics in the process of skill acquisition by trials and errors. We conclude this chapter with motor control related parables told by N. A. Bernstein to one of the authors (VMZ).more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/s22197417
