Explore the vast range of titles available.

Abstract The passive elastic properties of a muscle–tendon complex are usually estimated from the relationship between the joint angle and the passive resistive torque, although the properties of the different structures crossing the joint cannot be easily assessed. This study aimed to determine the passive mechanical properties of the gastrocnemius medialis muscle (GM) using supersonic shear imaging (SSI) that allows the measurement of localized muscle shear modulus ( μ ). The SSI of the GM was taken for 7 subjects during passive ankle dorsiflexion at a range of knee positions performed on an isokinetic dynamometer. The relationship between normalized μ and the length of the gastrocnemius muscle–tendon units (GMTU) was very well fitted to an exponential model (0.944< R ²<1) to calculate muscle stiffness ( α ) and slack length ( l0 ). This relationship was compared to the normalized force–length relationship obtained using Hoang's model. In addition, the reliability of the μ -length obtained with the knee fully extended was calculated. The μ -length relationship was highly correlated with the force–length (0.964< R ²<0.992) although muscle force was slightly underestimated (RMSE=31.0±14.7 N, range: 7.8–56.0 N). α and l0 measured with the knee extended were similar to that reconstructed from all knee angles and displayed good intra-session reliability (for α, SEM: 9.7 m−1 ; CV: 7.5%; ICC: 0.652; for l0 , SEM: 0.002 m; CV: 0.4%; ICC: 0.992). These findings indicate that SSI may provide an indirect estimation of passive muscle force, and highlight its clinical applicability to evaluate the passive properties of mono- and bi-articular muscles.

Abstract Although muscle–tendon slack length is a crucial parameter used in muscle models, this is one of the most difficult measures to estimate in vivo. The aim of this study was to determine the onset of the rise in tension ( i.e ., slack length) during passive stretching in both Achilles tendon and gastrocnemius medialis. Muscle and tendon shear elastic modulus was measured by elastography (supersonic shear imaging) during passive plantarflexion (0° and 90° of knee angle, 0° representing knee fully extended, in a random order) in 9 participants. The within-session repeatability of the determined slack length was good at 90° of knee flexion ( SEM =3.3° and 2.2° for Achilles tendon and gastrocnemius medialis, respectively) and very good at 0° of knee flexion ( SEM =1.9° and 1.9° for Achilles tendon and gastrocnemius medialis, respectively). The slack length of gastrocnemius medialis was obtained at a significantly lower plantarflexed angle than for Achilles tendon at both 0° ( P <0.0001; mean difference =19.4±3.8°) and 90° of knee flexion ( P <0.0001; mean difference =25.5±7.6°). In conclusion, this study showed that the joint angle at which the tendon falls slack can be experimentally determined using supersonic shear imaging. The slack length of gastrocnemius medialis and Achilles tendon occurred at different joint angles. Although reporting this result is crucial to a better understanding of muscle–tendon interactions, further experimental investigations are required to explain this result.

The purpose of the present study was to determine whether subjects who have learned a complex motor skill exhibit similar neuromuscular control strategies. We studied a population of experienced gymnasts during backward giant swings on the high bar. This cyclic movement is interesting because it requires learning, as untrained subjects are unable to perform this task. Nine gymnasts were tested. Both kinematics and electromyographic (EMG) patterns of 12 upper-limb and trunk muscles were recorded. Muscle synergies were extracted by non-negative matrix factorization (NMF), providing two components: muscle synergy vectors and synergy activation coefficients. First, the coefficient of correlation (r) and circular cross-correlation (r(max)) were calculated to assess similarities in the mechanical patterns, EMG patterns, and muscle synergies between gymnasts. We performed a further analysis to verify that the muscle synergies (in terms of muscle synergy vectors or synergy activation coefficients) extracted for one gymnast accounted for the EMG patterns of the other gymnasts. Three muscle synergies explained 89.9 ± 2.0% of the variance accounted for (VAF). The coefficients of correlation of the muscle synergy vectors among the participants were 0.83 ± 0.08, 0.86 ± 0.09, and 0.66 ± 0.28 for synergy #1, #2, and #3, respectively. By keeping the muscle synergy vectors constant, we obtained an averaged VAF across all pairwise comparisons of 79 ± 4%. For the synergy activation coefficients, r(max)-values were 0.96 ± 0.03, 0.92 ± 0.03, and 0.95 ± 0.03, for synergy #1, #2, and #3, respectively. By keeping the synergy activation coefficients constant, we obtained an averaged VAF across all pairwise comparisons of 72 ± 5%. Although variability was found (especially for synergy #3), the gymnasts exhibited gross similar neuromuscular strategies when performing backward giant swings. This confirms that the muscle synergies are consistent across participants, even during a skilled motor task that requires learning.

During stretching studies, surface electromyography (sEMG) is used to ensure the passive state of the muscle, for the characterization of passive muscle mechanical properties. Different thresholds (1%, 2% or 5% of maximal) are indifferently used to set “passive state”. This study aimed to investigate the effects of a slight activity on the joint and muscle mechanical properties during stretching. The joint torque and muscle shear modulus of the triceps surae muscles were measured in fifteen healthy volunteers during ankle dorsiflexions: (i) in a “fully relaxed” state, (ii) during active conditions where participants were asked to produce an sEMG amplitude of 1%, 2% or 5% of their maximal sEMG amplitude of the triceps surae. The 1% condition was the only that did not result in significant differences in joint torque or shear modulus compared to the relaxed condition. In the 2% condition, increases in joint torque were found at 80% of the maximal angle in dorsiflexion, and in the shear modulus of gastrocnemius medialis and gastrocnemius lateralis at the maximal angle in dorsiflexion. During the 5% condition, joint torque and the shear modulus of gastrocnemius medialis were higher than during relaxed condition at angles larger than 40% of maximal angle in dorsiflexion. The results provide new insights on the thresholds that should be considered for the design of stretching studies. A threshold of 1% seems much more appropriate than a 2% or 5% threshold in healthy participants. Further studies are required to define similar thresholds for patients.

Skeletal muscle is the engine that powers what is arguably the most essential and defining feature of human and animal life—locomotion. Muscles function to change length and produce force to enable movement, posture, and balance. Despite this seemingly simple role, skeletal muscle displays a variety of phenomena that still remain poorly understood. These phenomena are complex—the result of interactions between active and passive machinery, as well as mechanical, chemical and electrical processes. The emergence of imaging technologies over the past several decades has led to considerable discoveries regarding how skeletal muscles function in vivo where activation levels are submaximal, and the length and velocity of contracting muscle fibres are transient. However, our knowledge of the mechanisms of muscle behaviour during everyday human movements remains far from complete. In this review, we discuss the principal advancements in imaging technology that have led to discoveries to improve our understanding of in vivo muscle function over the past 50 years. We highlight the knowledge that has emerged from the development and application of various techniques, including ultrasound imaging, magnetic resonance imaging, and elastography to characterise muscle design and mechanical properties. We emphasize that our inability to measure the forces produced by skeletal muscles still poses a significant challenge, and that future developments to accurately and reliably measure individual muscle forces will promote newfrontiers in biomechanics, physiology, motor control, and robotics. Finally, we identify critical gaps in our knowledge and future challenges that we hope can be solved as a biomechanics community in the next 50 years.

Individual differences in the distribution of activation between synergist muscles have been reported during a wide variety of tasks. Whether these differences represent actual individual strategies is unknown. The aims of this study were to: (i) test the between-day reliability of the distribution of activation between synergist muscles, (ii) to determine the robustness of these strategies between tasks, and to (iii) describe the inter-individual variability of activation strategies in a large sample size. Eighty-five volunteers performed a series of single-joint isometric tasks with their dominant leg [knee extension and plantarflexion at 25% of maximal voluntary contraction (MVC)] and locomotor tasks (pedalling and walking). Of these participants, 62 performed a second experimental session that included the isometric tasks. Myoelectrical activity of six lower limb muscles (the three superficial heads of the quadriceps and the three heads of the triceps surae) was measured using surface electromyography (EMG) and normalized to that measured during MVC. When considering isometric contractions, distribution of normalized EMG amplitude among synergist muscles, considered here as activation strategies, was highly variable between individuals (15.8% < CV < 42.7%) and robust across days (0.57 < ICC < 0.82). In addition, individual strategies observed during simple single-joint tasks were correlated with those observed during locomotor tasks [0.37 <  r  < 0.76 for quadriceps ( n  = 83); 0.30 <  r  < 0.66 for triceps surae ( n  = 82); all P  < 0.001]. Our results provide evidence that people who bias their activation to a particular muscle do so during multiple tasks. Even though inter-individual variability of EMG signals has been well described, it is often considered noise which complicates the interpretation of data. This study provides evidence that variability results from actual differences in activation strategies.

Abstract Although elastography has been increasingly used for evaluating muscle shear modulus associated with age, sex, musculoskeletal, and neurological conditions, its physiological meaning is largely unknown. This knowledge gap may hinder data interpretation, limiting the potential of using elastography to gain insights into muscle biomechanics in health and disease. We derived a mathematical model from a widely-accepted Hill-type passive force–length relationship to gain insight about the physiological meaning of resting shear modulus of skeletal muscles under passive stretching, and validated the model by comparing against the ex-vivo animal data reported in our recent work ( Koo et al. 2013 ). The model suggested that resting shear modulus of a slack muscle is a function of specific tension and parameters that govern the normalized passive muscle force–length relationship as well as the degree of muscle anisotropy. The model also suggested that although the slope of the linear shear modulus–passive force relationship is primarily related to muscle anatomical cross-sectional area (i.e. the smaller the muscle cross-sectional area, the more the increase in shear modulus to result in the same passive muscle force), it is also governed by the normalized passive muscle force–length relationship and the degree of muscle anisotropy. Taken together, although muscle shear modulus under passive stretching has a strong linear relationship with passive muscle force, its actual value appears to be affected by muscle’s mechanical, material, and architectural properties. This should be taken into consideration when interpreting the muscle shear modulus values.

Purpose The neck extensor muscles contribute to spinal support and posture while performing head and neck motion. Muscle stiffness relates to passive elasticity (support) and active tensioning (posture and movement) of muscle. It was hypothesized that support and motion requirements are reflected in the distribution of stiffness between superficial and deep neck extensor muscles. Methods In ten healthy participants, shear modulus (stiffness) of five neck extensor muscles was determined in prone at rest and during isometric head lift at three intensities using shear wave elastography. Results Shear modulus differed between muscles ( P  < 0.001), and was larger for the deeper muscles: (median (interquartile range)) trapezius 7.7 kPa (4.4), splenius capitis 6.5 kPa (2.5), semispinalis capitis 8.9 kPa (2.8), semispinalis cervicis 9.5 kPa (2.5), multifidus 14.9 kPa (1.4). Shear modulus differed between the resting condition and head lift ( P  < 0.001) but not between levels of head lift intensity. Conclusion Shear wave elastography revealed highest passive and active stiffness of the deep neck extensor muscles most close to the spine. The highest active increase of stiffness during the head lift was found in the semispinalis cervicis muscle. The non-invasive, clinically applicable estimates of muscle stiffness have potential for the assessment of muscular changes associated with neck pain/injury.

Abstract Peripheral nerves are exposed to mechanical stress during movement. However the in vivo mechanical properties of nerves remain largely unexplored. The primary aim of this study was to characterize the effect of passive dorsiflexion on sciatic nerve shear wave velocity (an index of stiffness) when the knee was in 90° flexion (knee 90°) or extended (knee 180°). The secondary aim was to determine the effect of five repeated dorsiflexions on the nerve shear wave velocity. Nine healthy participants were tested. The repeatability of sciatic nerve shear wave velocity was good for both knee 90° and knee 180° (ICCs≥0.92, CVs≤8.1%). The shear wave velocity of the sciatic nerve significantly increased ( p <0.0001) during dorsiflexion when the knee was extended (knee 180°), but no changes were observed when the knee was flexed (90°). The shear wave velocity–angle relationship displayed a hysteresis for knee 180°. Although there was a tendency for the nerve shear wave velocity to decrease throughout the repetition of the five ankle dorsiflexions, the level of significance was not reached ( p =0.055). These results demonstrate that the sciatic nerve stiffness can be non-invasively assessed during passive movements. In addition, the results highlight the importance of considering both the knee and the ankle position for clinical and biomechanical assessment of the sciatic nerve. This non-invasive technique offers new perspectives to provide new insights into nerve mechanics in both healthy and clinical populations (e.g., specific peripheral neuropathies).

Stretching is widely used in sport training and clinical practice with the aim of increasing muscle-tendon extensibility and joint range of motion. The underlying assumption is that extensibility increases as a result of increased passive tension applied to muscle-tendon units. In some stretching protocols, this condition is not always met sufficiently to trigger adaptation within the muscle-tendon unit. For example, there is experimental evidence that both acute and chronic stretching interventions may increase the maximal range of motion in the absence of changes in the passive torque-angle curve. We contend that these results are partly explained by the influence of non-muscular structures that contribute only marginally to the passive torque. The potential candidates are the nervous system and fasciae, which would play an important role in the perception of the stretch and in the limitation of the range of motion of the maximal joints. At least in part, this may explain the lack of a significant effect of some chronic stretching interventions to change passive muscle tension.