Muscle Activation Dynamics Research Articles

Muscle activation and deactivation dynamics in Parkinson’s disease patients

Muscle activation and deactivation dynamics in Parkinson’s disease patients

Universal spectral profile and dynamic evolution of muscle activation: a hallmark of muscle type and physiological state.

The skeletal muscle is an integrated multicomponent system with complex dynamics of continuous myoelectrical activation of various muscle types across time scales to facilitate muscle coordination among units and adaptation to physiological states. To understand the multiscale dynamics of neuromuscular activity, we investigated spectral characteristics of different muscle types across time scales and their evolution with physiological states. We hypothesized that each muscle type is characterized by a specific spectral profile, reflecting muscle composition and function, that remains invariant over time scales and is universal across subjects. Furthermore, we hypothesized that the myoelectrical activation and corresponding spectral profile during certain movements exhibit an evolution path in time that is unique for each muscle type and reflects responses in muscle dynamics to exercise, fatigue, and aging. To probe the multiscale mechanism of neuromuscular regulation, we developed a novel protocol of repeated squat exercise segments, each performed until exhaustion, and we analyzed differentiated spectral power responses over a range of frequency bands for leg and back muscle activation in young and old subjects. We found that leg and back muscle activation is characterized by muscle-specific spectral profiles, with differentiated frequency band contribution, and a muscle-specific evolution path in response to fatigue and aging that is universal across subjects in each age group. The uncovered universality among subjects in the spectral profile of each muscle at a given physiological state, as well as the robustness in the evolution of these profiles over a range of time scales and states, reveals a previously unrecognized multiscale mechanism underlying the differentiated response of distinct muscle types to exercise-induced fatigue and aging.NEW & NOTEWORTHY To understand coordinated function of distinct fibers in a muscle, we investigated spectral dynamics of muscle activation during maximal exercise across a range of frequency bands and time scales of observation. We discovered a spectral profile that is specific for each muscle type, robust at short, intermediate, and large time scales, universal across subjects, and characterized by a muscle-specific evolution path with accumulation of fatigue and aging, indicating a previously unrecognized multiscale mechanism of muscle tone regulation.

Characterizing Motor Control of Mastication With Soft Actor-Critic.

The human masticatory system is a complex functional unit characterized by a multitude of skeletal components, muscles, soft tissues, and teeth. Muscle activation dynamics cannot be directly measured on live human subjects due to ethical, safety, and accessibility limitations. Therefore, estimation of muscle activations and their resultant forces is a longstanding and active area of research. Reinforcement learning (RL) is an adaptive learning strategy which is inspired by the behavioral psychology and enables an agent to learn the dynamics of an unknown system via policy-driven explorations. The RL framework is a well-formulated closed-loop system where high capacity neural networks are trained with the feedback mechanism of rewards to learn relatively complex actuation patterns. In this work, we are building on a deep RL algorithm, known as the Soft Actor-Critic, to learn the inverse dynamics of a simulated masticatory system, i.e., learn the activation patterns that drive the jaw to its desired location. The outcome of the proposed training procedure is a parametric neural model which acts as the brain of the biomechanical system. We demonstrate the model's ability to navigate the feasible three-dimensional (3D) envelope of motion with sub-millimeter accuracies. We also introduce a performance analysis platform consisting of a set of quantitative metrics to assess the functionalities of a given simulated masticatory system. This platform assesses the range of motion, metabolic efficiency, the agility of motion, the symmetry of activations, and the accuracy of reaching the desired target positions. We demonstrate how the model learns more metabolically efficient policies by integrating a force regularization term in the RL reward. We also demonstrate the inverse correlation between the metabolic efficiency of the models and their agility and range of motion. The presented masticatory model and the proposed RL training mechanism are valuable tools for the analysis of mastication and other biomechanical systems. We see this framework's potential in facilitating the functional analyses aspects of surgical treatment planning and predicting the rehabilitation performance in post-operative subjects.

Distinct sensorimotor feedback loops for dynamic and static control of primate precision grip

Volitional limb motor control involves dynamic and static muscle actions. It remains elusive how such distinct actions are controlled through separated or shared neural circuits. Here we explored the potential separation for dynamic and static controls in primate hand actions, by investigating the neuronal coherence between local field potentials (LFPs) of the spinal cord and the forelimb electromyographic activity (EMGs), and LFPs of the motor cortex and the EMGs during the performance of a precision grip in macaque monkeys. We observed the emergence of beta-range coherence with EMGs at spinal cord and motor cortex in the separated phases; spinal coherence during the grip phase and cortical coherence during the hold phase. Further, both of the coherences were influenced by bidirectional interactions with reasonable latencies as beta oscillatory cycles. These results indicate that dedicated feedback circuits comprising spinal and cortical structures underlie dynamic and static controls of dexterous hand actions.

Static stretch and dynamic muscle activity induce acute similar increase in corticospinal excitability.

Even though the acute effects of pre-exercise static stretching and dynamic muscle activity on muscular and functional performance have been largely investigated, their effects on the corticospinal pathway are still unclear. For that reason, this study examined the acute effects of 5×20 s of static stretching, dynamic muscle activity and a control condition on spinal excitability, corticospinal excitability and plantar flexor neuromuscular properties. Fifteen volunteers were randomly tested on separate days. Transcranial magnetic stimulation was applied to investigate corticospinal excitability by recording the amplitude of the motor-evoked potential (MEP) and the duration of the cortical silent period (cSP). Peripheral nerve stimulation was applied to investigate (i) spinal excitability using the Hoffmann reflex (Hmax), and (ii) neuromuscular properties using the amplitude of the maximal M-wave (Mmax) and corresponding peak twitch torque. These measurements were performed with a background 30% of maximal voluntary isometric contraction. Finally, the maximal voluntary isometric contraction torque and the corresponding electromyography (EMG) from soleus, gastrocnemius medialis and gastrocnemius lateralis were recorded. These parameters were measured immediately before and 10 s after each conditioning activity of plantar flexors. Corticospinal excitability (MEP/Mmax) was significantly enhanced after static stretching in soleus (P = 0.001; ES = 0.54) and gastrocnemius lateralis (P<0.001; ES = 0.64), and after dynamic muscle activity in gastrocnemius lateralis (P = 0.003; ES = 0.53) only. On the other hand, spinal excitability (Hmax/Mmax), cSP duration, muscle activation (EMG/Mmax) as well as maximal voluntary and evoked torque remained unaltered after all pre-exercise interventions. These findings indicate the presence of facilitation of the corticospinal pathway without change in muscle function after both static stretching (particularly) and dynamic muscle activity.

Complexity, Composition, and Control of Bipedal Balancing Movements as the Postural Control System Adapts to Unstable Support Surfaces or Altered Feet Positions

The current project investigated the dynamics of postural movements and muscle activity during balancing with feet-together and feet-apart positions on different support surfaces (firm surface (FS), modified- and conventional balance boards). We hypothesized that movement complexity and muscle activation would increase with increased balance-task difficulty, and that differences in the composition and control of postural movements between bipedal wide- and narrow-based balancing would be observed in all surface conditions. We applied a principal component analysis (PCA) to decompose postural movement trajectories of 26 active-young adults into sets of movement components (principal movements; PMs). Three PCA-based variables were calculated for each PM: the cumulative relative variance as a measure of movement complexity; the relative explained variance as a measure of the composition of postural movements; and the PM-acceleration as a measure for the control of the movement components. The main results revealed that both movement complexity and muscle activity increased with increased balance-task difficulty, of which altering support surfaces yielded more and greater effects than changing feet positions. Only on the FS, different movement structures were observed between narrowed- and wide-based standing (p ≤ 0.016); whereas different control of PMs was observed on all surfaces (p < 0.05). Standing on the stable surface illustrated opposite control behaviors compared to balancing on both multiaxial-unstable surfaces. In summary, on stable surface, changing the feet position affected inter-segment coordination. On unstable surfaces, the postural control system appeared to maintain inter-segment coordination characteristics, while the adaptation was confined to the sensorimotor integration processes.

Dynamics of forearm muscle activity in slanted computer mice use.

Static muscular activity of muscles activated in the use of the conventional PC mouse is believed to represent a higher risk for the musculoskeletal health of the user than dynamic muscular activity. This paper presents a compounded muscular activity dynamics indicator (akin to percent relative range), enabling comparison between computer handheld pointing devices. This muscular dynamism approach considers baseline muscular activity (APL, ECR, ECU and ED) relative to the Maximum Voluntary Contraction as well as the dynamics of muscular activation. The latter is computed as the ratio of the difference between APDF90 and APDF10 divided by APDF50 (APDF-Amplitude Probability Distribution Function for the 90th, 50th and 10th percentiles). The paper demonstrates the approach with results of comparative evaluation of a horizontal, a slanted and a vertical PC mouse, through surface EMG monitoring of 20 participants performing standardized graphical task with the devices. Hand size impacts muscular activity dynamics in these four muscles, which supersedes differences in device geometry, across the range of devices tested. Smaller devices relative to hand size foster more dynamic muscular activity.

Characterization of Spastic Ankle Flexors Based on Viscoelastic Modeling for Accurate Diagnosis

Characterization of the musculoskeletal system is essential for diagnosis providing the implications for therapy corresponding to causes of the diseases. This paper presents a characterization of an ankle neuromuscular system of patients with spasticity, to provide quantitative pathological level of the ankle spasticity with biomechanical and neurological disorders. Measurements from manual spasticity evaluation combined with a suggested neuromuscular model and parameter optimization process enabled a reliable characterization of the spastic ankle flexors. The model included two non-neural parameters representing the viscoelasticity of the muscle and four neural parameters showing the dynamics of muscle activation and corresponding force only using the measured joint angle and resistance torque. Torque contributions from non-neural parameters especially elastic properties of muscle was greater than 50% of the overall torque, common in both patients with spasticity and healthy controls. Among subgroups of the patients, subjects with short post diseases period less than 5 years, had higher torque contribution level from neural components more than 50% of the overall torque compared to the patients with longer post diseases period more than 10 years who had overall torque less than 30% of the total estimated torque. We concluded that proposed model based ankle flexor characterization served as a tools for diagnosing the patients with spasticity corresponding to their causes of diseases with both quantified neural and non-neural parameters.

A systems-theoretic analysis of low-level human motor control: application to a single-joint arm model.

Continuous control using internal models appears to be quite straightforward explaining human motor control. However, it demands both, a high computational effort and a high model preciseness as the whole trajectory needs to be converted. Intermittent control shows great promise for avoiding these drawbacks of continuous control, at least to a certain extent. In this contribution, we study intermittency at the motoneuron level. We ask: how many different, but constant muscle stimulation sets are necessary to generate a stable movement for a specific motor task? Intermittent control, in our perspective, can be assumed only if the number of transitions is relatively small. As application case, a single-joint arm movement is considered. The muscle contraction dynamics is described by a Hill-type muscle model, for the muscle activation dynamics both Hatze's and Zajac's approach are considered. To actuate the lower arm, up to four muscle groups are implemented. A systems-theoretic approach is used to find the smallest number of transitions between constant stimulation sets. A method for a stability analysis of human motion is presented. A Lyapunov function candidate is specified. Thanks to sum-of-squares methods, the presented procedure is generally applicable and computationally feasible. The region-of-attraction of a transition point, and the number of transitions necessary to perform stable arm movements are estimated. The results support the intermittent control theory on this level of motor control, because only very few transitions are necessary.

Evaluation of linear and non-linear activation dynamics models for insect muscle.

In computational modelling of sensory-motor control, the dynamics of muscle contraction is an important determinant of movement timing and joint stiffness. This is particularly so in animals with many slow muscles, as is the case in insects—many of which are important models for sensory-motor control. A muscle model is generally used to transform motoneuronal input into muscle force. Although standard models exist for vertebrate muscle innervated by many motoneurons, there is no agreement on a parametric model for single motoneuron stimulation of invertebrate muscle. Although several different models have been proposed, they have never been evaluated using a common experimental data set. We evaluate five models for isometric force production of a well-studied model system: the locust hind leg tibial extensor muscle. The response of this muscle to motoneuron spikes is best modelled as a non-linear low-pass system. Linear first-order models can approximate isometric force time courses well at high spike rates, but they cannot account for appropriate force time courses at low spike rates. A linear third-order model performs better, but only non-linear models can account for frequency-dependent change of decay time and force potentiation at intermediate stimulus frequencies. Some of the differences among published models are due to differences among experimental data sets. We developed a comprehensive toolbox for modelling muscle activation dynamics, and optimised model parameters using one data set. The “Hatze-Zakotnik model” that emphasizes an accurate single-twitch time course and uses frequency-dependent modulation of the twitch for force potentiation performs best for the slow motoneuron. Frequency-dependent modulation of a single twitch works less well for the fast motoneuron. The non-linear “Wilson” model that optimises parameters to all data set parts simultaneously performs better here. Our open-access toolbox provides powerful tools for researchers to fit appropriate models to a range of insect muscles.

Efficiency of Pneumatic Tourniquet Cuff With Asymmetric Pressure Distribution at Rest and During Isometric Muscle Action

Ipavec, M, Grapar Žargi, T, Jelenc, J, and Kacin, A. Efficiency of pneumatic tourniquet cuff with asymmetric pressure distribution at rest and during isometric muscle action. J Strength Cond Res 33(9): 2570-2578, 2019-The aim of this study was to compare effects of newly designed double-chamber cuff with asymmetric pressure (APC) distribution and standard single-chamber cuff with symmetric pressure (SPC) distribution on muscle perfusion and volitional activation. First, the 2 cuffs were compared bilaterally on resting thigh muscles of 17 healthy volunteers at 4 cuff pressures (120, 160, 200, and 240 mm Hg). Then, the subjects performed the isometric endurance test of knee extensor muscles to volitional failure at 40% of maximal volitional isometric action in both free-flow and blood flow restricted condition. Changes in hemoglobin kinetics in vastus lateralis muscle (near-infrared spectroscopy), surface electromyography of vastus medialis muscle, and pain intensity (visual analogue scale [VAS]) were continuously recorded. At rest, a significant difference (p = 0.009) in velocity of change in total hemoglobin concentration was noted between the cuffs at 160 mm Hg (APC = 0.028 μM·s and SPC = 0.056 μM·s). The VAS scores significantly increased (p = 0.031) at pressures ≥200 mm Hg, with no difference between the cuffs. Duration of isometric action with blood flow restriction was 12% shorter (p = 0.003) than in free-flow condition, with no difference between the cuffs. There were no significant differences in muscle activation or hemoglobin kinetics between the exercise conditions or cuff types. The results show that APC reduces blood flow in quadriceps femoris muscle at rest at lower pressure than SPC, which suggests its enhanced efficiency for blood flow restriction. Given that application of either type of cuff during sustained isometric action had only minor impact on muscle endurance and oxygen kinetics, future research must focus primarily on dynamic muscle actions.

토탭 운동이 동적균형과 큰볼기근의 근활성에 미치는 영향

토탭 운동이 동적균형과 큰볼기근의 근활성에 미치는 영향

Time Course of Changes in Neuromuscular Parameters During Maximal Bilateral Dynamic Muscle Actions

Time Course of Changes in Neuromuscular Parameters During Maximal Bilateral Dynamic Muscle Actions

A review of simulation methods for human movement dynamics with emphasis on gait

Human gait analysis is a complex problem in biomechanics because of highly nonlinear human motion equations, muscle dynamics, and foot-ground contact. Despite a large number of studies in human gait analysis, predictive human gait simulation is still challenging researchers to increase the accuracy and computational efficiency for evaluative studies (e.g., model-based assistive device controllers, surgical intervention planning, athletic training, and prosthesis and orthosis design). To assist researchers in this area, this review article classifies recent predictive simulation methods for human gait analysis according to three categories: (1) the human models used (i.e., skeletal, musculoskeletal and neuromusculoskeletal models), (2) problem formulation, and (3) simulation solvers. Human dynamic models are classified based on whether muscle activation and/or contraction dynamics or joint torques (instead of muscle dynamics) are employed in the analysis. Different formulations use integration and/or differentiation or implicit-declaration of the dynamic equations. A variety of simulation solvers (i.e., semi- and fully-predictive simulation methods) are studied. Finally, the pros and cons of the different formulations and simulation solvers are discussed.

Cross-limb dynamics of postural tremor due to limb loading to fatigue: neural overflow but not coupling.

Many experiments have shown independence of the index finger dynamics under bilateral postural tremor protocols. Here we investigated in young adults the dynamics of bilateral multidirectional postural tremor and forearm muscle activity under the progressively fatiguing conditions supporting an external weight to the point of induced postural failure. When no loads were applied, tremor in the vertical (VT) and mediolateral (ML) directions was similar with prominent peaks within 2- to 4-Hz and 8- to 12-Hz bandwidths. Contrastingly tremor in the anterior-posterior (AP) direction was characterized by a single peak between 0 and 2 Hz. Although no tremor coupling occurred cross limbs, strong within-limb coupling was found between ML and VT directions when no loads were applied (coherence range: 0.77-0.85), implying that these oscillations are related and likely derived from mechanical sources. Applying an external load to the index finger(s) led to significant increases in the amplitude of VT tremor and EMG activity within that limb but also caused increases in tremor directions not aligned with the gravitational vector (AP and ML). Significant increases in VT and ML tremor and EMG activity in the contralateral (unloaded) limb were also found when a single index finger was loaded; however, this bilateral increase did not align with increases in interlimb coupling (coherence <0.21). The effects of fatigue caused by prolonged loading were widespread, affecting tremor and muscle activity in both limbs through a combination of neural and mechanical mechanisms. The single- and dual-limb loading to fatigue increased neural overflow but not tremor coupling between the index fingers.NEW & NOTEWORTHY This study investigated bilateral multidirectional tremor under unloaded and loaded conditions. We found that tremor in the mediolateral and vertical directions within a limb were strongly coupled, a result not reported previously. Furthermore, when holding a weight to failure, tremor in all directions increased. Tremor also increased in the contralateral (unloaded) limb despite no interlimb coupling. This contralateral increase in tremor following loading a limb until fatigue is hypothesized to stem from motor-overflow effects.

The comparison of dynamic postural control and muscle activity in time domain in athletes with and without chronic ankle instability

The comparison of dynamic postural control and muscle activity in time domain in athletes with and without chronic ankle instability

Effects of selective strengthening of tibialis posterior and stretching of iliopsoas on navicular drop, dynamic balance, and lower limb muscle activity in pronated feet: A randomized clinical trial

ABSTRACTObjectives: Flexibility and strength are compromised in pronated feet, which could in turn lead to alteration of the dynamic balance and muscle activity in the lower extremities. This study aimed to analyze the effects of selective tibialis posterior strengthening and iliopsoas stretching on navicular drop, dynamic balance, and lower limb muscle activity in young adults with pronated feet.Methods: Twenty-eight participants with pronated feet were randomly assigned to either the stretching and strengthening group (n = 14) or the conventional exercise group (n = 14). The stretching and strengthening group performed tibialis posterior strengthening exercises and iliopsoas stretching three times a week for 6 weeks in addition to the conventional towel curl exercises. The conventional exercise group performed towel curl exercises only. Navicular drop, dynamic balance, and lower limb muscle activity were assessed at baseline and post-intervention. A mixed model analysis of variance was performed to test the study hypothesis.Results: Significant group effects for the activity of tibialis anterior (p = 0.003) and abductor hallucis muscle (p = 0.010), as well as for the posterolateral (p = 0.036) and composite reach scores (p = 0.018), were detected. Significant group × time interactions were observed for naviculardrop (p < 0.001), all dynamic balance components (p < 0.001), and the activity of tibialis anterior (p < 0.001) and abductor hallucis (p < 0.001).Conclusions: This study demonstrated that inclusion of selective tibialis posterior strengthening and iliopsoas stretching in addition to the conventional towel curl exercise program could improve important clinical outcomes, such as navicular drop, muscle activity, and dynamic balance in flatfeet.

Change of Pain, Lumbar Sagittal Alignment and Multifidus after Sling Exercise Therapy for Patients with Chronic Low Back Pain

Purpose: This study examined the effects of sling exercise therapy on vertebral alignment, VAS, muscle activity, and multifidus of patients with chronic low back pain. Methods: Simple random sampling was used to divide the patients (n=116) into the sling exercise therapy group (SETG) and conservative physical therapy group (CPTG), with each group provided a intervention program in 3 sessions a week for 12 weeks. The lumbar lordosis angle (LLA), lumbar intervertebral disc angle (LIVDA) for vertebral alignment, lumbar muscle activity, and multifidus atrophy were measured before and after the intervention. Results: SETG showed significant changes in LLA, LIVDA of rate of change (delta score), and in relieving pain. The right-left balance gap for the lumbar dynamic muscle activity decreased after the intervention. The SETG showed significant changes in the grade of lumbar multifidus atrophy. Conclusion: The sling exercise therapy program is an effective exercise therapy method on vertebral alignment, muscle activity, recovery from multifidus atrophy, and pain relief for patients with chronic low back pain.

Identifying the Dynamics of Leg Muscle Activation During Human Gait Using Neural Oscillator and Fuzzy Compensator

Background: The goal of this study is to design a model in order to predict the muscle activation pattern because the muscle activation patterns contain valuable information about the muscle dynamics and movement patterns. Therefore, the goal of the presentation of this neural model is to identify the desired muscle activation patterns by Hopf chaotic oscillator during walking. Since the knee muscles activation has a significant effect on the movement pattern during walking, the main concentration of this study is to identify the knee muscles activation dynamics using a modeling technique. Methods: The electromyography (EMG) recording obtained from 5 healthy subjects that electrodes positioned on the tibialis-anterior (TA) and rectus femoris muscles on every 2 feet. In the proposed model, along with the chaotic oscillator, a fuzzy compensator was designed to face the unmolded dynamics. In fact, on the condition, the observed difference between the desired and actual activation patterns violate some specific quantitative ranges, the fuzzy compensator based on predefined rules modify the activity pattern produced by the Hopf oscillator. Results: Some quantitative measures used to evaluate the results. According to the achieved results, the proposed model could generate the trajectories, dynamics of which are similar to the muscle activation dynamics of the studied muscles. In this model, the generated activity pattern by the proposed model cannot follow the desired activity of the TA muscle as well as rectus femoris muscle. Conclusion: The similarity between the generated activity pattern by the model and the activation dynamics of Rectus- Femoris muscle was more in comparison with the similarity observed between activation pattern of Tibialis- Anterior and the pattern generated by the model. In other words, based on the recorded human data, the activation pattern of the Rectus- Femoris is more similar to a rhythmic pattern.

Model-based analysis of fatigued human knee extensors

This study investigated the effect of isometrically induced fatigue on Hill-type muscle model parameters and related task-dependent effects. Parameter identification methods were used to extract fatigue-related parameter trends from isometric and ballistic dynamic maximum voluntary knee extensions. Nine subjects, who completed ten fatiguing sets, each consisting of nine 3 s isometric maximum voluntary contractions with 3 s rest plus two ballistic contractions with different loads, were analyzed. Only at the isometric task, the identified optimized model parameter values of muscle activation rate and maximum force generating capacity of the contractile element decreased from 20.8 pm 8.4 to 11.2 pm 4.1 Hz and from 18{,}137 pm 150 to 10{,}666 pm 2139 N, respectively. For all tasks, the maximum efficiency of the contractile element, mathematically related to the curvature of the force–velocity relation, increased from 0.35 pm 0.04 to 0.42 pm 0.05. The model parameter maximum contraction velocity decreased from 0.93 pm 0.1 to 0.9 pm 0.1 m/s and the stiffness of the serial elastic element from 1936 pm 227 to 1432 pm 245 N/mm. Thus, models of fatigue should consider fatigue dependencies in active as well as in passive elements, and muscle activation dynamics should account for the task dependency of fatigue.