Killian Bouillard

Characterization of passive elastic properties of the human medial gastrocnemius muscle belly using supersonic shear imaging

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<R²<1) to calculate muscle stiffness (α) and slack length (l(0)). This relationship was compared to the normalized force-length relationship obtained using Hoangs 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<R²<0.992) although muscle force was slightly underestimated (RMSE=31.0±14.7 N, range: 7.8-56.0 N). α and l(0) 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 l(0), 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.

Supersonic shear imaging provides a reliable measurement of resting muscle shear elastic modulus.

The aim of the present study was to assess the reliability of shear elastic modulus measurements performed using supersonic shear imaging (SSI) in nine resting muscles (i.e. gastrocnemius medialis, tibialis anterior, vastus lateralis, rectus femoris, triceps brachii, biceps brachii, brachioradialis, adductor pollicis obliquus and abductor digiti minimi) of different architectures and typologies. Thirty healthy subjects were randomly assigned to the intra-session reliability (n = 20), inter-day reliability (n = 21) and the inter-observer reliability (n = 16) experiments. Muscle shear elastic modulus ranged from 2.99 (gastrocnemius medialis) to 4.50 kPa (adductor digiti minimi and tibialis anterior). On the whole, very good reliability was observed, with a coefficient of variation (CV) ranging from 4.6% to 8%, except for the inter-operator reliability of adductor pollicis obliquus (CV = 11.5%). The intraclass correlation coefficients were good (0.871 ± 0.045 for the intra-session reliability, 0.815 ± 0.065 for the inter-day reliability and 0.709 ± 0.141 for the inter-observer reliability). Both the reliability and the ease of use of SSI make it a potentially interesting technique that would be of benefit to fundamental, applied and clinical research projects that need an accurate assessment of muscle mechanical properties.

Estimation of Individual Muscle Force Using Elastography

Background Estimation of an individual muscle force still remains one of the main challenges in biomechanics. In this way, the present study aimed: (1) to determine whether an elastography technique called Supersonic Shear Imaging (SSI) could be used to estimate muscle force, (2) to compare this estimation to that one provided by surface electromyography (EMG), and (3) to determine the effect of the pennation of muscle fibers on the accuracy of the estimation. Methods and Results Eleven subjects participated in two experimental sessions; one was devoted to the shear elastic modulus measurements and the other was devoted to the EMG recordings. Each session consisted in: (1) two smooth linear torque ramps from 0 to 60% and from 0 to 30% of maximal voluntary contraction, for the first dorsal interosseous and the abductor digiti minimi, respectively (referred to as “ramp contraction”); (2) two contractions done with the instruction to freely change the torque (referred to as “random changes contraction”). Multi-channel surface EMG recordings were obtained from a linear array of eight electrodes and the shear elastic modulus was measured using SSI. For ramp contractions, significant linear relationships were reported between EMG activity level and torque (R2 = 0.949±0.036), and between shear elastic modulus and torque (R2 = 0.982±0.013). SSI provided significant lower RMSdeviation between measured torque and estimated torque than EMG activity level for both types of contraction (1.4±0.7 vs. 2.8±1.4% of maximal voluntary contraction for “ramp contractions”, p<0.01; 4.5±2.3 vs. 7.9±5.9% of MVC for “random changes contractions”, p<0.05). No significant difference was reported between muscles. Conclusion The shear elastic modulus measured using SSI can provide a more accurate estimation of individual muscle force than surface EMG. In addition, pennation of muscle fibers does not influence the accuracy of the estimation.

Shear elastic modulus can be used to estimate an index of individual muscle force during a submaximal isometric fatiguing contraction

The present study was designed to determine whether fatigue alters the ability to estimate an index of individual muscle force from shear elastic modulus measurements (experiment I), and to test the ability of this technique to highlight changes in load sharing within a redundant muscle group during an isometric fatiguing task (experiment II). Twelve subjects participated in experiment I, which consisted of smooth linear torque ramps from 0 to 80% of maximal voluntary contraction (MVC) performed before and after an isometric fatigue protocol, beginning at 40% of MVC and stopped when the force production dropped below 30% of MVC. Although the relationships between modulus and torque were very similar for pre- and postfatigue [root mean square deviation (RMS(deviation)) = 3.7 ± 2.6% of MVC], the relationships between electromyography activity level and torque were greatly altered by fatigue (RMS(deviation) = 10.3 ± 2.6% of MVC). During the fatiguing contraction, shear elastic modulus provided a significantly lower RMS(deviation) between measured torque and estimated torque than electromyography activity level (5.7 ± 0.9 vs. 15.3 ± 3.8% of MVC). Experiment II performed with eight participants consisted of an isometric knee extension at 25% of MVC sustained until exhaustion. Opposite changes in shear elastic modulus were observed between synergists (vastus medialis, vastus lateralis, and rectus femoris) of some participants, reflecting changes in load sharing. In conclusion, despite the fact that we did not directly estimate muscle force (in Newtons), this is the first demonstration of an experimental technique to accurately quantify relative changes in force in an individual human muscle during a fatiguing contraction.

Evidence of changes in load sharing during isometric elbow flexion with ramped torque

This study aimed to: (1) test the repeatability of Supersonic Shear Imaging measures of muscle shear elastic modulus of four elbow flexor muscles during isometric elbow flexion with ramped torque; (2) determine the relationship between muscle shear elastic modulus and elbow torque for the four elbow flexor muscles, and (3) investigate changes in load sharing between synergist elbow flexor muscles with increases in elbow flexor torque. Ten subjects performed ten isometric elbow flexions consisting of linear torque ramps of 30-s from 0 to 40% of maximal voluntary contraction. The shear elastic modulus of each elbow flexor muscle (biceps brachii long head [BB(LH)], biceps brachii short head [BB(SH)], brachialis [BA], and brachoradialis [BR]) and of triceps brachii long head [TB] was measured twice with individual muscles recorded in separate trials in random order. A good repeatability of the shape of the changes in shear elastic modulus as a function of torque was found for each elbow flexor muscle (r-values: 0.85 to 0.94). Relationships between the shear elastic modulus and torque were best explained by a second order polynomial, except BA where a higher polynomial was required. Statistical analysis showed that BB(SH) and BB(LH) had an initial slow change at low torques followed by an increasing rate of increase in modulus with higher torques. In contrast, the BA shear elastic modulus increased rapidly at low forces, but plateaued at higher forces. These results suggest that changes in load sharing between synergist elbow flexors could partly explain the non-linear EMG-torque relationship classically reported for BB during isometric efforts.

Muscle shear elastic modulus is linearly related to muscle torque over the entire range of isometric contraction intensity

Muscle shear elastic modulus is linearly related to muscle torque during low-level contractions (<60% of Maximal Voluntary Contraction, MVC). This measurement can therefore be used to estimate changes in individual muscle force. However, it is not known if this relationship remains valid for higher intensities. The aim of this study was to determine: (i) the relationship between muscle shear elastic modulus and muscle torque over the entire range of isometric contraction and (ii) the influence of the size of the region of interest (ROI) used to average the shear modulus value. Ten healthy males performed two incremental isometric little finger abductions. The joint torque produced by Abductor Digiti Minimi was considered as an index of muscle torque and elastic modulus. A high coefficient of determination (R(2)) (range: 0.86-0.98) indicated that the relationship between elastic modulus and torque can be accurately modeled by a linear regression over the entire range (0% to 100% of MVC). The changes in shear elastic modulus as a function of torque were highly repeatable. Lower R(2) values (0.89±0.13 for 1/16 of ROI) and significantly increased absolute errors were observed when the shear elastic modulus was averaged over smaller ROI, half, 1/4 and 1/16 of the full ROI) than the full ROI (mean size: 1.18±0.24cm(2)). It suggests that the ROI should be as large as possible for accurate measurement of muscle shear modulus.

Effect of vastus lateralis fatigue on load sharing between quadriceps femoris muscles during isometric knee extensions

The present study aimed to investigate the effects of selective fatigue (i.e., one muscle of the quadriceps) on load sharing strategies during submaximal knee extensions. Shear wave elastography was used to measure muscle shear elastic modulus, as this is considered to be an index of individual muscle force. Sixteen participants attended two experimental sessions that each involved six 10-s knee extensions at 20% of maximal voluntary contraction (MVC) followed by a sustained submaximal isometric knee extension at 20% of MVC, until task failure (Tlim). Between the 10-s contractions and Tlim, participants were required to rest (5 min) for the control session or underwent 5 min of electromyostimulation (EMS) on vastus lateralis (EMS session). Compared with the control session, vastus lateralis shear elastic modulus values were significantly lower after EMS considering both the start of Tlim (54.6 ± 11.8 vs. 68.4 ± 19.2 kPa; P = 0.011) and the entire Tlim contraction (59.0 ± 14.0 vs. 74.4 ± 20.3 kPa; P = 0.019). However, no significant differences were observed for the other recorded muscles (vastus medialis and rectus femoris; both P = 1), i.e., different patterns of changes were found between participants. In conclusion, this study demonstrates that prefatiguing a single agonist muscle does not lead to a consistent redistribution of load sharing among the quadriceps muscles between individuals. These results suggest that the central nervous system does not use a common principle among individuals to control load sharing when neuromuscular fatigue occurs.

The electromyographic fatigue threshold is not a valid tool to assess muscle function

The present study aimed at determining the electromyographic fatigue threshold (EMG(FT)) from the EMG activity level and the EMG frequency content of the First Dorsal Interosseous. Thirty-seven healthy subjects performed seven isometric index abductions at randomly ordered percentages of maximal voluntary contraction (i.e., 20%, 25%, 30%, 35%, 40%, 50% and 60%). During these bouts, surface EMG was measured using a linear electrodes array (i.e., seven EMG channels) in the First Dorsal Interosseous. For each subject the EMG(FT) was determined from both Root Mean Square (RMS) and Mean Power Frequency (MPF) values, only if the following criteria were met: (i) significant positive linear regression (P<0.05) between force and slope coefficient, (ii) an adjusted coefficient of determination for force versus slope coefficient relationship greater than 0.85, and (iii) a standard error for the EMG(FT) below 5% of MVC. The results showed the inability to determine an EMG(FT) in all of the 37 subjects from both RMS (9 out of 37 subjects) and MPF (27 out of 37 subjects). In addition, for the 12 subjects tested twice, the reproducibility of the EMG(FT) determination was weak (ICC=-0.029 and SEM=7.5% of MVC for EMG(FT) determined from MPF). The present results suggest that the EMG(FT) is not a valid tool to assess muscle function.

Prediction of time-to-exhaustion in the first dorsal interosseous muscle from early changes in surface electromyography parameters.

Introduction: In this study we evaluated the precision of the time‐to‐exhaustion (Tlim) prediction from the early changes in surface electromyography (sEMG) of the first dorsal interosseous muscle. Methods: Thirty subjects performed an index finger isometric abduction at 35% of maximal voluntary contraction (MVC) until exhaustion. Ten participants performed the same exercise at 50% MVC 1 week later. Changes in sEMG parameters across time were modeled using the area‐ratio and the linear regression slope. Tlim was plotted as a function of each of these indices of change, and the coefficient of determination (R2) was determined. Results: Null to moderate R2 (0.22 and 0.56 at 35% and 50% MVC, respectively) values were calculated. The best Tlim estimation led to a high prediction error (21.6 ± 15.0% of Tlim for the 50% MVC task). Conclusions: Although the prediction of time‐to‐exhaustion is an appealing research topic, these results suggest that it cannot be done solely from sEMG. Muscle Nerve 45: 835–840, 2012