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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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Abstracts From the 2018 Annual Meeting
Muscle weakness and loss of independent joint control are the 2 most common neuromotor impairments after stroke. While there are a number of approaches to improve poststroke muscle weakness, there are currently no rehabilitation strategies that directly target a patient’s inability to match and independently activate the normal patterned muscle coordination strategies, or “muscle synergies.” Our goal is to develop an EMG-based controller for retraining healthy muscle synergies in patients with stroke-related disabilities. The controller can be integrated into rehabilitation robots for their ability to structure the robot’s force output based on input EMG activity. However, developing such a controller would require a clear understanding of the relationship between the applied force from a rehabilitation robot and the resulting changes to a patient’s muscle synergies. Therefore, this study was performed to quantify how the muscle synergies of horizontal planar-reaching are affected by direction of an applied force at the end-effector (ie, hand). A 2 DOF, 10 muscle model was developed in MATLAB using parameters obtained from the OpenSim (version 3.3) open source software system. Simulation experiments were then performed in MATLAB to investigate the relationship between the applied force and the resulting muscle synergies. The simulated event was composed of several trials of the same righthanded, planar, multidirectional reaching task from 0° (to the right) to 360°. Each trial applied a different steering force direction at the subject’s hand, varying from −45° to 45° relative to the reaching direction. The simulation trials were also validated by evaluating the EMG patterns of a healthy subject when performing the same reaching task with varying steering force directions. For the 0° steering force trials, the muscle synergies and their activation timings were extracted using nonnegative matrix factorization (NMF). For all other trials, the synergy matrix was fixed and the activation timings were extracted from the product of the EMG of that trial and the pseudo-inverse of the synergy matrix from the 0° steering force trial. By fixing the synergy matrix in the trials with steering forces, we can directly track activation changes of a certain synergy as steering force is varied. For both simulation and experimental trials, circular statistics revealed a linear relationship between changes in steering force direction and principal direction of synergy activation. These results suggest that the activation of a synergy can be controlled directly by the direction of an applied steering force. This has relevant implications in synergy-based controller design because a computer can easily manipulate a patient’s muscle synergies and track the changes while avoiding the computational expense of NMF. In addition, similar analysis could be used to extract the relationship between applied forces and changes in synergies for other types of motion.
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- Award ID(s):
- 1804053
- PAR ID:
- 10091274
- Date Published:
- Journal Name:
- Neurorehabilitation and Neural Repair
- Volume:
- 32
- Issue:
- 12
- ISSN:
- 1545-9683
- Page Range / eLocation ID:
- 1110
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Synergy analysis via dimensionality reduction is a standard approach in biomechanics to capture the dominant features of limb kinematics or muscle activation signals, which can be called “coarse synergies.” Here we demonstrate that the less dominant features of these signals, which are often explicitly disregarded or considered noise, can nevertheless exhibit “fine synergies” that reveal subtle, yet functionally important, adaptations. To find the coarse synergies, we applied non-negative matrix factorization (NMF) to unilateral EMG data from eight muscles of the involved leg in ten people with drop-foot (DF), and of the right leg of 16 unimpaired (control) participants. We then extracted the fine synergies for each group by removing the coarse synergies (i.e., first two factors explaining 85% of variance) from the data and applying Principal Component Analysis (PCA) to those residuals. Surprisingly, the time histories and structure of the coarse EMG synergies showed few differences between DF and controls—even though the kinematics of drop-foot gait is evidently different from unimpaired gait. In contrast, the structure of the fine EMG synergies (as per their PCA loadings) showed significant differences between groups. In particular, loadings forTibialis Anterior,Peroneus Longus,Gastrocnemius Lateralis,BicepsandRectus Femoris,Vastus MedialisandLateralismuscles differed between groups ( ). We conclude that the multiple differences found in the structure of the fine synergies extracted from EMG in people with drop-foot vs. unimpaired controls—not visible in the coarse synergies—likely reflect differences in their motor strategies. Coarse synergies, in contrast, seem to mostly reflect the gross features of EMG in bipedal gait that must be met by all participants—and thus show few differences between groups. However, drawing insights into the clinical origin of these differences requires well-controlled clinical trials. We propose that fine synergies should not be disregarded in biomechanical analysis, as they may be more informative of the disruption and adaptation of muscle coordination strategies in participants due to drop-foot, age and/or other gait impairments.more » « less
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Abstract Patients with neuromuscular disease fail to produce necessary muscle force and have trouble maintaining joint moment required to perform activities of daily living. Measuring muscle force values in patients with neuromuscular disease is important but challenging. Electromyography (EMG) can be used to obtain muscle activation values, which can be converted to muscle forces and joint torques. Surface electrodes can measure activations of superficial muscles, but fine-wire electrodes are needed for deep muscles, although it is invasive and require skilled personnel and preparation time. EMG-driven modeling with surface electrodes alone could underestimate the net torque. In this research, authors propose a methodology to predict muscle activations from deeper muscles of the upper extremity. This method finds missing muscle activation one at a time by combining an EMG-driven musculoskeletal model and muscle synergies. This method tracks inverse dynamics joint moments to determine synergy vector weights and predict muscle activation of selected shoulder and elbow muscles of a healthy subject. In addition, muscle-tendon parameter values (optimal fiber length, tendon slack length, and maximum isometric force) have been personalized to the experimental subject. The methodology is tested for a wide range of rehabilitation tasks of the upper extremity across multiple healthy subjects. Results show this methodology can determine single unmeasured muscle activation up to Pearson's correlation coefficient (R) of 0.99 (root mean squared error, RMSE = 0.001) and 0.92 (RMSE = 0.13) for the elbow and shoulder muscles, respectively, for one degree-of-freedom (DoF) tasks. For more complicated five DoF tasks, activation prediction accuracy can reach up to R = 0.71 (RMSE = 0.29).more » « less
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Abstract BackgroundMuscle synergies, computationally identified intermuscular coordination patterns, have been utilized to characterize neuromuscular control and learning in humans. However, it is unclear whether it is possible to alter the existing muscle synergies or develop new ones in an intended way through a relatively short-term motor exercise in adulthood. This study aimed to test the feasibility of expanding the repertoire of intermuscular coordination patterns through an isometric, electromyographic (EMG) signal-guided exercise in the upper extremity (UE) of neurologically intact individuals. Methods10 participants were trained for six weeks to induce independent control of activating a pair of elbow flexor muscles that tended to be naturally co-activated in force generation. An untrained isometric force generation task was performed to assess the effect of the training on the intermuscular coordination of the trained UE. We applied a non-negative matrix factorization on the EMG signals recorded from 12 major UE muscles during the assessment to identify the muscle synergies. In addition, the performance of training tasks and the characteristics of individual muscles’ activity in both time and frequency domains were quantified as the training outcomes. ResultsTypically, in two weeks of the training, participants could use newly developed muscle synergies when requested to perform new, untrained motor tasks by activating their UE muscles in the trained way. Meanwhile, their habitually expressed muscle synergies, the synergistic muscle activation groups that were used before the training, were conserved throughout the entire training period. The number of muscle synergies activated for the task performance remained the same. As the new muscle synergies were developed, the neuromotor control of the trained muscles reflected in the metrics, such as the ratio between the targeted muscles, number of matched targets, and task completion time, was improved. ConclusionThese findings suggest that our protocol can increase the repertoire of readily available muscle synergies and improve motor control by developing the activation of new muscle coordination patterns in healthy adults within a relatively short period. Furthermore, the study shows the potential of the isometric EMG-guided protocol as a neurorehabilitation tool for aiming motor deficits induced by abnormal intermuscular coordination after neurological disorders. Trial registrationThis study was registered at the Clinical Research Information Service (CRiS) of the Korea National Institute of Health (KCT0005803) on 1/22/2021.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1177/1545968318817151
