Intra-Subject and Inter-Subject Movement Variability Quantified with Muscle Synergies in Upper-Limb Reaching Movements

Zhao, Kunkun; Zhang, Zhisheng; Wen, Haiying; Scano, Alessandro

doi:10.3390/biomimetics6040063

Cited by 25 publications

(30 citation statements)

References 76 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Regarding the similarity between participants, our findings presented the median values of similarity ranging from 0.73 to 0.86 for five trunk muscle synergies (W) and from 0.64 to 0.75 for their temporal patterns (C). These inter-cluster similarities appear to be greater than those in highly variable upper-limb movements found in a previous study, although the similarity of temporal patterns was not assessed 22 , 55 . This suggests that trunk muscle synergies have more robust features as the trunk requires both stability and movement even in the loosely constrained task scenario, compared with the upper limbs, which primarily function as a wide range of manipulations with many degrees of freedom and involve motor cortical neurons with complex and heterogeneous motor patterns 39 .…”

Section: Discussioncontrasting

confidence: 80%

Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals

Saito

Yokoyama

Sasaki

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Muscle synergy analysis is useful for investigating trunk coordination patterns based on the assumption that the central nervous system reduces the dimensionality of muscle activation to simplify movement. This study aimed to quantify the variability in trunk muscle synergy during various trunk motor tasks in healthy participants to provide reference data for evaluating trunk control strategies in patients and athletes. Sixteen healthy individuals performed 11 trunk movement and stability tasks with electromyography (EMG) recording of their spinal and abdominal muscles (6 bilaterally). Non-negative matrix factorization applied to the concatenated EMG of all tasks identified the five trunk muscle synergies (W) with their corresponding temporal patterns (C). The medians of within-cluster similarity defined by scalar products in W and rmax coefficient using the cross-correlation function in C were 0.73–0.86 and 0.64–0.75, respectively, while the inter-session similarities were 0.81–0.96 and 0.74–0.84, respectively. However, the lowest and highest values of both similarity indices were broad, reflecting the musculoskeletal system’s redundancy within and between participants. Furthermore, the significant differences in the degree of variability between the trunk synergies may represent the different neural features of synergy organization and strategies to overcome the various mechanical demands of a motor task.

show abstract

Section: Discussioncontrasting

confidence: 80%

Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals

Saito

Yokoyama

Sasaki

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Regarding the similarity between participants, our ndings presented the median values of similarity ranging from 0.73 to 0.86 for ve trunk muscle synergies (W) and from 0.64 to 0.75 for their temporal patterns (C). These inter-cluster similarities appear to be greater than those in highly variable upper-limb movements found in a previous study, although the similarity of temporal patterns was not assessed 20,50 . This suggests that trunk muscle synergies have more robust features as the trunk requires both stability and movement even in the loosely constrained task scenario, compared with the upper limbs, which primarily function as a wide range of manipulations with many degrees of freedom and involve motor cortical neurons with complex and heterogeneous motor patterns 33 .…”

Section: Discussioncontrasting

confidence: 74%

“…Furthermore, some level of variability between sessions can also be attributed to experimental protocols, including the fact that electrodes were not placed on each trunk muscle in exactly the same way between sessions, or other physical factors, such as skin conditions and fatigue 17,56 . Thus, variability due to experimental factors needs to be considered when evaluating motor control strategies in different populations in longitudinal studies with multiple sessions 50 .…”

Section: Discussionmentioning

confidence: 99%

Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals

Saito

Yokoyama

Sasaki

et al. 2022

Preprint

View full text Add to dashboard Cite

Muscle synergy analysis is a useful approach for investigating the nature of trunk coordination patterns based on the assumption that the central nervous system reduces the dimensionality of muscle activation to simplify movement. This study aimed to quantify the variability in trunk muscle synergy during 11 trunk motor tasks in healthy participants to provide reference data for evaluating trunk control strategies in patients and athletes. Even in a highly variable task context, the five trunk muscle synergies with their temporal patterns presented well-reconstructed original electromyography data. While the variability in trunk synergies between participants and sessions were comparable to those for other body parts in previous studies, these metrics had a broad range, reflecting some level of redundancy of the musculoskeletal system in healthy individuals. Furthermore, the significant differences in the degree of variability between the trunk synergies may reflect the different neural features of trunk synergy organization and strategies to overcome the various mechanical demands of a motor task. The quantification of the variability of trunk muscle synergy may guide the assessment of stereotypes or diverse features of trunk control strategies and the interpretation of adaptability in the presence of diseases or the process of motor training in future research.

show abstract

“…Because of the limitations of superficial electromyography (e.g., lack of access to deep muscles), we have developed an 18-muscle 3-D model of the human lumbar spine to estimate muscular activity. Furthermore, it has been reported that separation of muscle activation into a tonic component (responsible for producing anti-gravitational joint torque for maintaining postural stability) and a phasic component (responsible for producing dynamic joint torque by including the effect of velocity and acceleration/deceleration of movement) allows for better evaluation of muscle activation and subsequently muscular synergies (7, 20, 21).…”

Section: Introductionmentioning

confidence: 99%

Lumbar time-varying muscle synergies in trunk flexion and bending movements at different velocities

Rouchi

Davoudi

Meftahi

et al. 2022

Preprint

View full text Add to dashboard Cite

PurposeAlthough the extent of which the central nervous system uses muscle synergies as a movement control strategy remains an open area of research, it is widely agreed that synergies facilitate the robustness of the neuromuscular system, allowing for effective postural control and flexible movement. This work aimed to investigate the muscle activation patterns of the trunk and time-varying muscle synergies using a novel 18-muscle 3-DOF, 3-D musculoskeletal model of the lumbar spine developed by the authors.Methods24 different biaxial trunk movements were simulated via the optimization of kinetic and kinematic measures towards obtaining the corresponding muscle activation patterns at 3 different velocities. These patterns were subsequently used to extract the principal (phasic and tonic) spatio-temporal synergies associated with the observed muscle activation patterns in the range of simulated movements.ResultsFour dominant synergies were able to explain a considerable percent (about 75%) of the variance of the simulated muscle activities. The extracted synergies were spatially tuned in the direction of the main simulated movements (flexion/extension and right/left lateral bending). The temporal patterns demonstrated gradual monotonic shifts in tonic synergies and biphasic modulatory components in phasic synergies with spatially tuned time-delays. The increase in velocity resulted in an elevated amplitude coefficient and accelerated activation of phasic synergies.ConclusionOur results suggest the plausibility of a time-varying synergies strategy in the dynamic control of trunk movement. Further work is needed to explore leveraging these concepts in various applications, such as rehabilitation and musculoskeletal biomechanics, towards providing more insight into the mechanisms underlying trunk stability and flexibility.

show abstract

Intra-Subject and Inter-Subject Movement Variability Quantified with Muscle Synergies in Upper-Limb Reaching Movements

Cited by 25 publications

References 76 publications

Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals

Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals

Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals

Lumbar time-varying muscle synergies in trunk flexion and bending movements at different velocities

Contact Info

Product

Resources

About