Tacit representation of muscle activities during coordination training: Muscle synergy analysis to visualize motor enhancement in virtual trajectory of multi-joint arm movement

Koba, Keitaro; Murakami, Kenta; Oku, Tatsuo; Uno, Kanna; Phatiwuttipat, Pipatthana; Yamashita, Yuto; Uemura, Mamoru; Hirai, Hiroaki; Miyazaki, Fumio

doi:10.1109/biorob.2014.6913788

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…The physics-based approach is a powerful way to reverse engineer the control mechanism underlying the neuromusculoskeletal system in the dynamic environment. For more details on muscle synergies based on the AA concept, refer also to our recent publications (Koba et al, 2014 ; Oku et al, 2014 , 2015 ; Uno et al, 2014 ).…”

Section: Discussionmentioning

confidence: 99%

On the Origin of Muscle Synergies: Invariant Balance in the Co-activation of Agonist and Antagonist Muscle Pairs

Hirai

Miyazaki

Koba

et al. 2015

Front. Bioeng. Biotechnol.

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Investigation of neural representation of movement planning has attracted the attention of neuroscientists, as it may reveal the sensorimotor transformation essential to motor control. The analysis of muscle synergies based on the activity of agonist–antagonist (AA) muscle pairs may provide insight into such transformations, especially for a reference frame in the muscle space. In this study, we examined the AA concept using the following explanatory variables: the AA ratio, which is related to the equilibrium-joint angle, and the AA sum, which is associated with joint stiffness. We formulated muscle synergies as a function of AA sums, positing that muscle synergies are composite units of mechanical impedance. The AA concept can be regarded as another form of the equilibrium-point (EP) hypothesis, and it can be extended to the concept of EP-based synergies. We introduce, here, a novel tool for analyzing the neurological and motor functions underlying human movements and review some initial insights from our results about the relationships between muscle synergies, endpoint stiffness, and virtual trajectories (time series of EP). Our results suggest that (1) muscle synergies reflect an invariant balance in the co-activation of AA muscle pairs; (2) each synergy represents the basis for the radial, tangential, and null movements of the virtual trajectory in the polar coordinates centered on the specific joint at the base of the body; and (3) the alteration of muscle synergies (for example, due to spasticity or rigidity following neurological injury) results in significant distortion of endpoint stiffness and concomitant virtual trajectories. These results indicate that muscle synergies (i.e., the balance of muscle mechanical impedance) are essential for motor control.

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Section: Discussionmentioning

confidence: 99%

On the Origin of Muscle Synergies: Invariant Balance in the Co-activation of Agonist and Antagonist Muscle Pairs

Hirai

Miyazaki

Koba

et al. 2015

Front. Bioeng. Biotechnol.

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“…The physics-based approach is a powerful way to reverse engineer the control mechanism underlying the neuromusculoskeletal system in the dynamic environment. For more details on muscle synergies based on the AA concept, refer also to our recent publications (Koba et al, 2014;Oku et al, 2014Oku et al, , 2015Uno et al, 2014).…”

Section: Physics-based Approach To Muscle-synergy Extractionmentioning

confidence: 99%

Applications of Synergies in Human Machine Interfaces

Vinjamuri¹,

Mao²,

Maybhate³

2019

Frontiers Research Topics

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Application of neural machine interface in individuals with chronic hemiparetic stroke is regarded as a great challenge, especially for classification of the hand opening and grasping during a functional upper extremity movement such as reach-to-grasp. The overall accuracy of classifying hand movements, while actively lifting the paretic arm, is subject to a significant reduction compared to the accuracy when the arm is fully supported. Such a reduction is believed to be due to the expression of flexion synergy, which couples shoulder abduction (SABD) with elbow/wrist and finger flexion, and is common in up to 60% of the stroke population. Little research has been done to develop methods to reduce the impact of flexion synergy on the classification of hand opening and grasping. In this study, we proposed a novel approach to classify hand opening and grasping in the context of the flexion synergy using a wavelet coherence-based filter. We first identified the frequency ranges where the coherence between the SABD muscle and wrist/finger flexion muscles is significant in each participant, and then removed the synergy-induced electromyogram (EMG) component with a subject-specific and muscle-specific coherence-based filter. The new approach was tested in 21 stroke individuals with moderate to severe motor impairments. Employing the filter, 14 participants gained improvement in classification accuracy with a range of 0.1 to 14%, while four showed 0.3 to 1.2% reduction. The remaining three participants were excluded from comparison due to the lack of significant coherence, thus no filters were applied. The improvement in classification accuracy is significant (p = 0.017) when the SABD loading equals 50% of the maximal torque. Our findings suggest that the coherence-based filters can reduce the impact of flexion synergy by removing the synergy-induced EMG component and have the potential to improve the overall classification accuracy of hand movements in individuals with poststroke flexion synergy.

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“…In these studies, the motor functions of the synergies or the relationship between muscle synergy, EP trajectory, and endpoint stiffness have not been clarified. Thus, we focused on the cooperative effect of agonist-antagonist (A-A) muscle pairs around a joint, which may be related to the EP or stiffness and may be a component of muscle synergy [9]- [12]. Our previous studies revealed that the ratio of the A-A muscle activity level (A-A ratio) representing a reciprocal command helps control the joint EP angle and that the sum of the A-A muscle activity level (A-A sum) representing a coactivation command helps regulate the joint stiffness; they are suitable for understanding the cooperation of muscles, EP, and stiffness.…”

Section: Introductionmentioning

confidence: 99%

A novel muscle synergy extraction method to explain the equilibrium-point trajectory and endpoint stiffness during human upper-limb movements on a horizontal plane

Uno

Oku

Phatiwuttipat

et al. 2014

5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics

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Based on the idea of synergy to explore the building blocks of movements, this study focused on the muscle space for reaching movements by human upper limbs on a horizontal plane to estimate the relationship among muscle synergies, equilibrium-point (EP) trajectories, and endpoint stiffness in two ways: (1) a novel estimation method that analyzes electromyographic signals under the concept of agonistantagonist (A-A) muscle pairs and (2) a conventional estimation method that uses mechanical perturbations. The experimental results suggest that (1) muscle activities of reaching movements by human upper limbs are represented by only three functional muscle synergies; (2) each muscle synergy balances the coactivations of A-A muscle pairs; (3) two of the muscle synergies are invariant bases that form an EP trajectory described in polar coordinates centered on a shoulder joint, where one is a composite unit for radial movement and the other is for angular movement; and (4) the third muscle synergy is the invariant basis for additional adjustment of the endpoint stiffness and has some influence on the direction and size of the endpoint stiffness ellipse.

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Tacit representation of muscle activities during coordination training: Muscle synergy analysis to visualize motor enhancement in virtual trajectory of multi-joint arm movement

Cited by 6 publications

References 14 publications

On the Origin of Muscle Synergies: Invariant Balance in the Co-activation of Agonist and Antagonist Muscle Pairs

On the Origin of Muscle Synergies: Invariant Balance in the Co-activation of Agonist and Antagonist Muscle Pairs

Applications of Synergies in Human Machine Interfaces

A novel muscle synergy extraction method to explain the equilibrium-point trajectory and endpoint stiffness during human upper-limb movements on a horizontal plane

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