scholarly journals Modeling and simulating the neuromuscular mechanisms regulating ankle and knee joint stiffness during human locomotion

2015 ◽  
Vol 114 (4) ◽  
pp. 2509-2527 ◽  
Author(s):  
Massimo Sartori ◽  
Marco Maculan ◽  
Claudio Pizzolato ◽  
Monica Reggiani ◽  
Dario Farina
Keyword(s):  
Muscle Activation ◽  
Joint Stiffness ◽  
Human Locomotion ◽  
Biological Tissues ◽  
Musculoskeletal Model ◽  
Theoretical Description ◽  
Knee Joints ◽  
Dynamic Simulations ◽  
Muscle Groups ◽  
The Individual

This work presents an electrophysiologically and dynamically consistent musculoskeletal model to predict stiffness in the human ankle and knee joints as derived from the joints constituent biological tissues (i.e., the spanning musculotendon units). The modeling method we propose uses electromyography (EMG) recordings from 13 muscle groups to drive forward dynamic simulations of the human leg in five healthy subjects during overground walking and running. The EMG-driven musculoskeletal model estimates musculotendon and resulting joint stiffness that is consistent with experimental EMG data as well as with the experimental joint moments. This provides a framework that allows for the first time observing 1) the elastic interplay between the knee and ankle joints, 2) the individual muscle contribution to joint stiffness, and 3) the underlying co-contraction strategies. It provides a theoretical description of how stiffness modulates as a function of muscle activation, fiber contraction, and interacting tendon dynamics. Furthermore, it describes how this differs from currently available stiffness definitions, including quasi-stiffness and short-range stiffness. This work offers a theoretical and computational basis for describing and investigating the neuromuscular mechanisms underlying human locomotion.

scholarly journals Model-based analysis of the stiffness of the wrist joint in active and passive conditions

2018 ◽  
Author(s):  
Andrea Zonnino ◽  
Fabrizio Sergi
Keyword(s):  
Crucial Role ◽  
Muscle Activation ◽  
Wrist Joint ◽  
Joint Stiffness ◽  
Musculoskeletal Model ◽  
Experimental Measurements ◽  
Active Components ◽  
Muscle Groups ◽  
Biomechanical Constraints ◽  
Amount Of Knowledge

ABSTRACTThe control of joint stiffness is a fundamental mechanism used to control human movements. While many studies have observed how stiffness is controlled for tasks involving shoulder and elbow motion, a limited amount of knowledge is available for wrist movements, though the wrist plays a crucial role in fine manipulation.We have developed a computational framework based on a realistic musculoskeletal model, which allows to calculate the passive and active components of the wrist joint stiffness. We first used the framework to validate the musculoskeletal model against experimental measurements of the passive wrist joint stiffness, and then to study the contribution of different muscle groups on the passive joint stiffness. We finally used the framework to study the effect of muscle co - contraction on the active joint stiffness.The results show that thumb and finger muscles play a crucial role in determining the passive wrist joint stiff - ness: in the neutral posture, the direction of maximum stiffness aligns with the experimental measurements, and the magnitude increases by 113% when they are included. Moreover, the analysis of the controllability of joint stiffness showed that muscle co - contraction positively correlates with the stiffness magnitude and negatively correlates with the variability of the stiffness orientation (p < 0.01 in both cases). Finally, an exhaustive search showed that with appropriate selection of a muscle activation strategy, the joint stiffness orientation can be arbitrarily modulated. This observation suggests the absence of biomechanical constraints on the controllability of the orientation of the wrist joint stiffness.

scholarly journals Model-Based Analysis of the Stiffness of the Wrist Joint in Active and Passive Conditions

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Andrea Zonnino ◽  
Fabrizio Sergi
Keyword(s):  
Crucial Role ◽  
Muscle Activation ◽  
Wrist Joint ◽  
Joint Stiffness ◽  
Musculoskeletal Model ◽  
Experimental Measurements ◽  
Active Components ◽  
Muscle Groups ◽  
Biomechanical Constraints ◽  
Amount Of Knowledge

The control of joint stiffness is a fundamental mechanism used to control human movements. While many studies have observed how stiffness is modulated for tasks involving shoulder and elbow motion, a limited amount of knowledge is available for wrist movements, though the wrist plays a crucial role in manipulation. We have developed a computational framework based on a realistic musculoskeletal model, which allows one to calculate the passive and active components of the wrist joint stiffness. We first used the framework to validate the musculoskeletal model against experimental measurements of the wrist joint stiffness, and then to study the contribution of different muscle groups to the passive joint stiffness. We finally used the framework to study the effect of muscle cocontraction on the active joint stiffness. The results show that thumb and finger muscles play a crucial role in determining the passive wrist joint stiffness: in the neutral posture, the direction of maximum stiffness aligns with the experimental measurements, and the magnitude increases by 113% when they are included. Moreover, the analysis of the controllability of joint stiffness showed that muscle cocontraction positively correlates with the stiffness magnitude and negatively correlates with the variability of the stiffness orientation (p < 0.01 in both cases). Finally, an exhaustive search showed that with appropriate selection of a muscle activation strategy, the joint stiffness orientation can be arbitrarily modulated. This observation suggests the absence of biomechanical constraints on the controllability of the orientation of the wrist joint stiffness.

scholarly journals An Analysis of Sport-Specific Pain Symptoms through Inter-Individual Training Differences in CrossFit

Sports ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 68
Author(s):  
Maria Bernstorff ◽  
Norman Schumann ◽  
Nader Maai ◽  
Thomas Schildhauer ◽  
Matthias Königshausen
Keyword(s):  
Online Survey ◽  
Personal Information ◽  
Gluteus Medius ◽  
Single Type ◽  
Training Methods ◽  
Personal Training ◽  
Muscle Groups ◽  
Small Muscle ◽  
The Individual ◽  
Pain Symptoms

Background: CrossFit is one of the fastest growing “high-intensity functional training” methods in recent years. Due to the very demanding motion sequences and high loads, it was initially assumed that there was an extremely high risk of injury. However, studies have shown that injury rates are given between 0.74–3.3 per 1000 h of training, which is not higher than in other individual sports such as weightlifting. The purpose of the study was to estimate the type of pain symptoms that are directly related to CrossFit, to estimate the frequency of injuries that occur within a population of recreational CrossFit athletes, and, finally, to identify the factors influencing the frequency of pain during CrossFit training. Methods: A total of 414 active CrossFit athletes completed an online survey inclusive of 29 items focusing on individual physical characteristics and training behavior, as well as simultaneous or previously practiced sports. Results: There was a significantly higher proportion of knee pain in athletes who had previously or simultaneously played another sport (p = 0.014). The duration, intensity, or type of personal training plan developed, along with personal information such as age, gender, or BMI, had no significant influence on the pain data. We could not find any significant variance between the groups that we formed based on the differently stated one-repetition max (RMs). There were differences in athletes who stated that they did specific accessory exercises for small muscle groups. Above all, athletes performing exercises for the hamstrings and the gluteus medius indicated fewer pain symptoms for the sacro-iliac joint (SIJ)/iliac and lower back locations. Conclusions: It is important not to see CrossFit as a single type of sport. When treating a CrossFit athlete, care should be taken to address inter-individual differences. This underlines the significant differences of this study between the individual athletes with regard to the ability to master certain skills or their previous sporting experience. The mere fact of mastering certain exercises seems to lead to significantly more pain in certain regions. In addition, there seems to be a connection between the previous or simultaneous participation in other sports and the indication of pain in the knee region.

Development of an Apparatus for Bilateral Rhythmical Training of Arm Movement Via Linear and Elliptical Trajectories of Various Directions

2014 ◽  
Vol 8 (3) ◽  
Author(s):  
Zlatko Matjačić ◽  
Matjaž Zadravec ◽  
Jakob Oblak
Keyword(s):  
Muscle Activation ◽  
Arm Movement ◽  
Emg Activity ◽  
Activation Patterns ◽  
Muscle Activation Patterns ◽  
Arm Cycling ◽  
Arm Reaching ◽  
Direction Of Movement ◽  
Muscle Groups ◽  
Neurologically Intact

Clinical rehabilitation of individuals with various neurological disorders requires a significant number of movement repetitions in order to improve coordination and restoration of appropriate muscle activation patterns. Arm reaching movement is frequently practiced via motorized arm cycling ergometers where the trajectory of movement is circular thus providing means for practicing a single and rather nonfunctional set of muscle activation patterns, which is a significant limitation. We have developed a novel mechanism that in the combination with an existing arm ergometer device enables nine different movement modalities/trajectories ranging from purely circular trajectory to four elliptical and four linear trajectories where the direction of movement may be varied. The main objective of this study was to test a hypothesis stating that different movement modalities facilitate differences in muscle activation patterns as a result of varying shape and direction of movement. Muscle activation patterns in all movement modalities were assessed in a group of neurologically intact individuals in the form of recording the electromyographic (EMG) activity of four selected muscle groups of the shoulder and the elbow. Statistical analysis of the root mean square (RMS) values of resulting EMG signals have shown that muscle activation patterns corresponding to each of the nine movement modalities significantly differ in order to accommodate to variation of the trajectories shape and direction. Further, we assessed muscle activation patterns following the same protocol in a selected clinical case of hemiparesis. These results have shown the ability of the selected case subject to produce different muscle activation patterns as a response to different movement modalities which show some resemblance to those assessed in the group of neurologically intact individuals. The results of the study indicate that the developed device may significantly extend the scope of strength and coordination training in stroke rehabilitation which is in current clinical rehabilitation practice done through arm cycling.

scholarly journals Alterations in muscle activation patterns during robot-assisted bilateral training: A pilot study

2018 ◽  
Vol 233 (2) ◽  
pp. 219-231 ◽  
Author(s):  
Bo Sheng ◽  
Lihua Tang ◽  
Shengquan Xie ◽  
Chao Deng ◽  
Yanxin Zhang
Keyword(s):  
Muscle Activation ◽  
Interaction Force ◽  
Robot Assisted ◽  
Activation Patterns ◽  
Recovery Processes ◽  
Muscle Activation Patterns ◽  
Bilateral Training ◽  
Muscle Groups ◽  
Highly Correlated ◽  
Training Protocols

Robot-assisted bilateral training is being developed as a new rehabilitation approach for stroke patients. However, there is still a lack of understanding of muscle functions when performing robot-assisted synchronous movements. The aim of this work is to explore the muscle activation patterns and the voluntary effort of participants during different robot-assisted bilateral training protocols. To this end, 10 healthy participants were recruited to take part in a 60-minute experiment. The experiment included two different bilateral exercises, and each exercise contained four different training protocols. Trajectories of the robots, interaction force and surface electromyogram signals were recorded during training. The results show that the robots do affect the muscle activation patterns during different training protocols and exercises rather than the controller. Specifically, the activity of muscles is reduced in robot-assisted training but is increased in active force involved robot-assisted training when compared to robot-unassisted training. Meanwhile, the voluntary effort of participants can be presented by the adjusted trajectories via the controller. In addition, the results also suggest that the activations for the same muscle groups in the left and right arms are highly correlated with each other in both exercises. Furthermore, the training protocols and methods developed in this work could be further extended in future clinical trials to investigate therapeutic outcomes for patients as well as to better understand bilateral recovery processes.

scholarly journals An individual-based mechanical model of cell movement in heterogeneous tissues and its coarse-grained approximation

2018 ◽  
Author(s):  
R. J. Murphy ◽  
P. R. Buenzli ◽  
R. E. Baker ◽  
M. J. Simpson
Keyword(s):  
Mechanical Model ◽  
Numerical Solutions ◽  
Cell Movement ◽  
Biological Tissues ◽  
Tissue Level ◽  
Cellular Level ◽  
Coarse Grained ◽  
Mechanical Heterogeneity ◽  
Single Scale ◽  
The Individual

AbstractMechanical heterogeneity in biological tissues, in particular stiffness, can be used to distinguish between healthy and diseased states. However, it is often difficult to explore relationships between cellular-level properties and tissue-level outcomes when biological experiments are performed at a single scale only. To overcome this difficulty we develop a multi-scale mathematical model which provides a clear framework to explore these connections across biological scales. Starting with an individual-based mechanical model of cell movement, we subsequently derive a novel coarse-grained system of partial differential equations governing the evolution of the cell density due to heterogeneous cellular properties. We demonstrate that solutions of the individual-based model converge to numerical solutions of the coarse-grained model, for both slowly-varying-in-space and rapidly-varying-in-space cellular properties. Applications of the model are discussed, including determining relative cellular-level properties and an interpretation of data from a breast cancer detection experiment.

scholarly journals Muscle activation patterns are more constrained and regular in treadmill than in overground human locomotion

2020 ◽  
Author(s):  
Ilaria Mileti ◽  
Aurora Serra ◽  
Nerses Wolf ◽  
Victor Munoz-Martel ◽  
Antonis Ekizos ◽  
...  
Keyword(s):  
Neural Control ◽  
Muscle Activation ◽  
Human Locomotion ◽  
Activation Patterns ◽  
Motor Primitives ◽  
Muscle Activation Patterns ◽  
Synergistic Activation ◽  
Clinical Environments ◽  
The Central Nervous System ◽  
Main Activity

AbstractThe use of motorized treadmills as convenient tools for the study of locomotion has been in vogue for many decades. However, despite the widespread presence of these devices in many scientific and clinical environments, a full consensus on their validity to faithfully substitute free overground locomotion is still missing. Specifically, little information is available on whether and how the neural control of movement is affected when humans walk and run on a treadmill as compared to overground. Here, we made use of linear and nonlinear analysis tools to extract information from electromyographic recordings during walking and running overground, and on an instrumented treadmill. We extracted synergistic activation patterns from the muscles of the lower limb via non-negative matrix factorization. We then investigated how the motor modules (or time-invariant muscle weightings) were used in the two locomotion environments. Subsequently, we examined the timing of motor primitives (or time-dependent coefficients of muscle synergies) by calculating their duration, the time of main activation, and their Hurst exponent, a nonlinear metric derived from fractal analysis. We found that motor modules were not influenced by the locomotion environment, while motor primitives resulted overall more regular in treadmill than in overground locomotion, with the main activity of the primitive for propulsion shifted earlier in time. Our results suggest that the spatial and sensory constraints imposed by the treadmill environment forced the central nervous system to adopt a different neural control strategy than that used for free overground locomotion. A data-driven indication that treadmills induce perturbations to the neural control of locomotion.

scholarly journals Lower complexity of motor primitives ensures robust control of high-speed human locomotion

2020 ◽  
Author(s):  
Alessandro Santuz ◽  
Antonis Ekizos ◽  
Yoko Kunimasa ◽  
Kota Kijima ◽  
Masaki Ishikawa ◽  
...  
Keyword(s):  
High Speed ◽  
Muscle Activation ◽  
Human Locomotion ◽  
Muscle Synergies ◽  
Activation Patterns ◽  
Motor Primitives ◽  
Muscle Activation Patterns ◽  
Relative Contribution ◽  
Muscle Activations ◽  
Low Dimensional

AbstractWalking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we investigated how humans synergistically activate muscles during locomotion at different submaximal and maximal speeds. We analysed the duration and complexity (or irregularity) over time of motor primitives, the temporal components of muscle synergies. We found that the challenge imposed by controlling high-speed locomotion forces the central nervous system to produce muscle activation patterns that are wider and less complex relative to the duration of the gait cycle. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that robust locomotion control at challenging speeds is achieved by modulating the relative contribution of muscle activations and producing less complex and wider control signals, whereas slow speeds allow for more irregular control.

scholarly journals Structure and mechanics of aegagropilae fiber network

2017 ◽  
Vol 114 (18) ◽  
pp. 4607-4612 ◽  
Author(s):  
Gautier Verhille ◽  
Sébastien Moulinet ◽  
Nicolas Vandenberghe ◽  
Mokhtar Adda-Bedia ◽  
Patrice Le Gal
Keyword(s):  
Mechanical Response ◽  
Posidonia Oceanica ◽  
Biological Tissues ◽  
Individual Response ◽  
Fiber Network ◽  
Friction Forces ◽  
Fiber Clustering ◽  
Wide Range ◽  
Natural Aggregates ◽  
The Individual

Fiber networks encompass a wide range of natural and manmade materials. The threads or filaments from which they are formed span a wide range of length scales: from nanometers, as in biological tissues and bundles of carbon nanotubes, to millimeters, as in paper and insulation materials. The mechanical and thermal behavior of these complex structures depends on both the individual response of the constituent fibers and the density and degree of entanglement of the network. A question of paramount importance is how to control the formation of a given fiber network to optimize a desired function. The study of fiber clustering of natural flocs could be useful for improving fabrication processes, such as in the paper and textile industries. Here, we use the example of aegagropilae that are the remains of a seagrass (Posidonia oceanica) found on Mediterranean beaches. First, we characterize different aspects of their structure and mechanical response, and second, we draw conclusions on their formation process. We show that these natural aggregates are formed in open sea by random aggregation and compaction of fibers held together by friction forces. Although formed in a natural environment, thus under relatively unconstrained conditions, the geometrical and mechanical properties of the resulting fiber aggregates are quite robust. This study opens perspectives for manufacturing complex fiber network materials.

Sign in / Sign up

Export Citation Format

Share Document