Muscle synergies enable accurate joint moment prediction using few electromyography sensors*

2021 ◽  
Author(s):  
Yi-Xing Liu ◽  
Elena M. Gutierrez-Farewik
Keyword(s):  
Joint Moment ◽  
Muscle Synergies

scholarly journals Proactive Modulation in the Spatiotemporal Structure of Muscle Synergies Minimizes Reactive Responses in Perturbed Landings

2021 ◽  
Vol 9 ◽  
Author(s):  
Victor Munoz-Martel ◽  
Alessandro Santuz ◽  
Sebastian Bohm ◽  
Adamantios Arampatzis
Keyword(s):  
Mechanical Loading ◽  
Hip Joint ◽  
Joint Moment ◽  
Muscle Synergies ◽  
Electromyographic Activity ◽  
Leg Muscles ◽  
Neuromotor Control ◽  
Unstable Surface ◽  
Muscle Loading ◽  
Weight Acceptance

Stability training in the presence of perturbations is an effective means of increasing muscle strength, improving reactive balance performance, and reducing fall risk. We investigated the effects of perturbations induced by an unstable surface during single-leg landings on the mechanical loading and modular organization of the leg muscles. We hypothesized a modulation of neuromotor control when landing on the unstable surface, resulting in an increase of leg muscle loading. Fourteen healthy adults performed 50 single-leg landings from a 30 cm height onto two ground configurations: stable solid ground (SG) and unstable foam pads (UG). Ground reaction force, joint kinematics, and electromyographic activity of 13 muscles of the landing leg were measured. Resultant joint moments were calculated using inverse dynamics and muscle synergies with their time-dependent (motor primitives) and time-independent (motor modules) components were extracted via non-negative matrix factorization. Three synergies related to the touchdown, weight acceptance, and stabilization phase of landing were found for both SG and UG. When compared with SG, the motor primitive of the touchdown synergy was wider in UG (p < 0.001). Furthermore, in UG the contribution of gluteus medius increased (p = 0.015) and of gastrocnemius lateralis decreased (p < 0.001) in the touchdown synergy. Weight acceptance and stabilization did not show any statistically significant differences between the two landing conditions. The maximum ankle and hip joint moment as well as the rate of ankle, knee, and hip joint moment development were significantly lower (p < 0.05) in the UG condition. The spatiotemporal modifications of the touchdown synergy in the UG condition highlight proactive adjustments in the neuromotor control of landings, which preserve reactive adjustments during the weight acceptance and stabilization synergies. Furthermore, the performed proactive control in combination with the viscoelastic properties of the soft surface resulted in a reduction of the mechanical loading in the lower leg muscles. We conclude that the use of unstable surfaces does not necessarily challenge reactive motor control nor increase muscle loading per se. Thus, the characteristics of the unstable surface and the dynamics of the target task must be considered when designing perturbation-based interventions.

scholarly journals Higher order tensor decomposition for proportional myoelectric control based on muscle synergies

2021 ◽  
Vol 67 ◽  
pp. 102523
Author(s):  
Ahmed Ebied ◽  
Eli Kinney-Lang ◽  
Javier Escudero
Keyword(s):  
Tensor Decomposition ◽  
Higher Order ◽  
Myoelectric Control ◽  
Muscle Synergies ◽  
Order Tensor

scholarly journals An Algorithm for Choosing the Optimal Number of Muscle Synergies during Walking

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3311
Author(s):  
Riccardo Ballarini ◽  
Marco Ghislieri ◽  
Marco Knaflitz ◽  
Valentina Agostini
Keyword(s):  
Motor Task ◽  
Optimal Number ◽  
The Other ◽  
Simulated Dataset ◽  
Muscle Synergies ◽  
Mean Square ◽  
Real Dataset ◽  
Traditional Approaches ◽  
Selection Of ◽  
Semg Signals

In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds.

Analysis of contribution of muscle synergies on sit-to-stand motion using musculoskeletal model

2013 ◽  
Author(s):  
Qi An ◽  
Yuki Ishikawa ◽  
Junki Nakagawa ◽  
Hiroyuki Oka ◽  
Hiroshi Yamakawa ◽  
...  
Keyword(s):  
Musculoskeletal Model ◽  
Muscle Synergies ◽  
Sit To Stand

scholarly journals Classification of abnormal muscle synergies during sit-to-stand motion in individuals with acute stroke

2021 ◽  
pp. 100055
Author(s):  
Hiroki Hanawa ◽  
Keisuke Hirata ◽  
Taku Miyazawa ◽  
Keisuke Kubota ◽  
Moeka Yokoyama ◽  
...  
Keyword(s):  
Acute Stroke ◽  
Muscle Synergies ◽  
Sit To Stand

scholarly journals Identification of Individual Muscle Length Parameters from Measurements of Passive Joint Moment Around the Ankle Joint

2012 ◽  
Vol 7 (2) ◽  
pp. 168-176 ◽  
Author(s):  
Hisashi NAITO ◽  
Yasushi AKAZAWA ◽  
Ayu MIURA ◽  
Takeshi MATSUMOTO ◽  
Masao TANAKA
Keyword(s):  
Ankle Joint ◽  
Muscle Length ◽  
Joint Moment ◽  
Passive Joint ◽  
Individual Muscle

scholarly journals Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives

2013 ◽  
Vol 7 ◽  
Author(s):  
Cristiano Alessandro ◽  
Ioannis Delis ◽  
Francesco Nori ◽  
Stefano Panzeri ◽  
Bastien Berret
Keyword(s):  
Muscle Synergies ◽  
Task Space ◽  
Input Space ◽  
And Robotics
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