Torque and mechanomyogram correlations during muscle relaxation: effects of fatigue and time-course of recovery

Influence of age on force and re-lengthening dynamics after tetanic stimulation withdrawal in the tibialis anterior muscle

PURPOSE

During alternate movements across a joint, the changeover from one direction of rotation to the opposite may be influenced by the delay and rate of tension reduction and the compliance to re-lengthening of the previously active muscle group. Given the aging process may affect the above-mentioned factors, this work aimed to compare the dynamics of both the ankle torque decline and muscle re-lengthening, mirrored by mechanomyogram (MMG), in the tibialis anterior because of its important role in gait.

METHODS

During the relaxation phase, after a supramaximal 35 Hz stimulation applied at the superficial motor point, in 20 young (Y) and 20 old (O) subjects, the torque (T) and MMG dynamics characteristics were measured.

RESULTS

The T and MMG analysis provided: (I) the beginning of the decay after cessation of stimulation (T: 22.51 ± 5.92 ms [Y] and 51.35 ± 15.21 ms [O]; MMG: 27.38 ± 6.93 ms [Y] and 61.41 ± 18.42 ms [O]); (II) the maximum rate of reduction (T: - 110.4 ± 45.56 Nm/s [Y] and - 52.72 ± 32.12 Nm/s [O]; MMG: - 24.47 ± 10.95 mm/s [Y] and - 13.76 ± 6.54 mm/s [O]); (III) the muscle compliance, measuring the MMG reduction of every 10% reduction of torque (bin 20-10%: 15.69 ± 7.5[Y] and 10.8 ± 3.3 [O]; bin 10-0%: 22.12 ± 10.3 [Y] and 17.58 ± 5.6 [O]).

CONCLUSION

Muscle relaxation results are different in Y and O and can be monitored by a non-invasive method measuring physiological variables of torque and re-lengthening dynamics at the end of the electromechanical coupling previously induced by the neuromuscular stimulation.

A non-volitional skeletal muscle endurance test measures functional changes associated with impaired blood flow

Introduction: An electrically stimulated intermittent fatigue test using mechanomyography was recently proposed as a possible tool for detecting clinically relevant changes in muscle function. This study was designed to determine whether the proposed test can detect additional fatigue when it should be present. Methods: Subjects (n = 10) underwent two trials each (occluded and normal blood flow) with a standardized fatigue protocol on the Ankle Dorsiflexors (AD) and Wrist Extensors (WE) using a clinical electrical stimulator. Results: Mean normalized twitch acceleration was strongly predictive of mean normalized torque (R ² = 0.828). The WE experienced lower twitch magnitudes throughout the tourniquet trial (10.81 ± 1.25 m/s²) compared to normal blood flow (18.05 ± 1.06 m/s²). The AD twitches were overall reduced in the tourniquet trial (3.87 ± 0.48 m/s²) compared with the control trial (8.57 ± 0.91 m/s²). Conclusion: Occluding blood flow to a muscle should cause greater muscle fatigue. The ability to detect reduced contraction magnitudes during an electrically stimulated fatigue protocol resulting from low blood flow suggests the proposed test may be capable of detecting clinically relevant muscle deficits.

Assessment of muscle activity using electrical stimulation and mechanomyography: a systematic review

This research has proved that mechanomyographic (MMG) signals can be used for evaluating muscle performance. Stimulation of the lost physiological functions of a muscle using an electrical signal has been determined crucial in clinical and experimental settings in which voluntary contraction fails in stimulating specific muscles. Previous studies have already indicated that characterizing contractile properties of muscles using MMG through neuromuscular electrical stimulation (NMES) showed excellent reliability. Thus, this review highlights the use of MMG signals on evaluating skeletal muscles under electrical stimulation. In total, 336 original articles were identified from the Scopus and SpringerLink electronic databases using search keywords for studies published between 2000 and 2020, and their eligibility for inclusion in this review has been screened using various inclusion criteria. After screening, 62 studies remained for analysis, with two additional articles from the bibliography, were categorized into the following: (1) fatigue, (2) torque, (3) force, (4) stiffness, (5) electrode development, (6) reliability of MMG and NMES approaches, and (7) validation of these techniques in clinical monitoring. This review has found that MMG through NMES provides feature factors for muscle activity assessment, highlighting standardized electromyostimulation and MMG parameters from different experimental protocols. Despite the evidence of mathematical computations in quantifying MMG along with NMES, the requirement of the processing speed, and fluctuation of MMG signals influence the technique to be prone to errors. Interestingly, although this review does not focus on machine learning, there are only few studies that have adopted it as an alternative to statistical analysis in the assessment of muscle fatigue, torque, and force. The results confirm the need for further investigation on the use of sophisticated computations of features of MMG signals from electrically stimulated muscles in muscle function assessment and assistive technology such as prosthetics control.

Acute effects of direct inhibitory pressure over the biceps brachii myotendinous junction on skeletal muscle activation and force output

Force (F) reduction is reported with myotendinous junction (MTJ) manipulation. Autogenic inhibition reflex (AIR) activation is supposed to be the main mechanism. Still, its role remains unclear. The study aimed at assessing the effects of MTJ direct inhibitory pressure (DIP) on neuromuscular activation and F in the elbow flexor (agonist) and extensor (antagonist) muscles. After maximum voluntary contraction (MVC) assessment, thirty-five participants randomly performed submaximal contractions at 20, 40, 60, and 80% MVC. Electromyographic (EMG), mechanomyographic (MMG), and F signals were recorded. Protocol was repeated under (i) DIP (10-s pressure on the biceps brachii MTJ) with the elbow at 120° (DIP₁₂₀), (ii) DIP with the elbow at 180° (DIP₁₈₀), and (iii) without DIP (Ctrl). Electromechanical delay (EMD) components, EMG and MMG root mean square (RMS), and rate of force development (RFD) were calculated. Independently from the angle, DIP induced decrements in MVC, RFD, and RMS of EMG and MMG signals and lengthened the EMD components in agonist muscles (P<0.05). The DIP-induced decrease in F output of the agonist muscles seems to be possibly due to a concomitant impairment of the neuromuscular activation and a transient decrease in stiffness. After DIP, the antagonist muscle displayed no changes; therefore, the intervention of AIR remains questionable.

Torque and mechanomyogram relationships during electrically-evoked isometric quadriceps contractions in persons with spinal cord injury

The interaction between muscle contractions and joint loading produces torques necessary for movements during activities of daily living. However, during neuromuscular electrical stimulation (NMES)-evoked contractions in persons with spinal cord injury (SCI), a simple and reliable proxy of torque at the muscle level has been minimally investigated. Thus, the purpose of this study was to investigate the relationships between muscle mechanomyographic (MMG) characteristics and NMES-evoked isometric quadriceps torques in persons with motor complete SCI. Six SCI participants with lesion levels below C4 [(mean (SD) age, 39.2 (7.9) year; stature, 1.71 (0.05) m; and body mass, 69.3 (12.9) kg)] performed randomly ordered NMES-evoked isometric leg muscle contractions at 30°, 60° and 90° knee flexion angles on an isokinetic dynamometer. MMG signals were detected by an accelerometer-based vibromyographic sensor placed over the belly of rectus femoris muscle. The relationship between MMG root mean square (MMG-RMS) and NMES-evoked torque revealed a very high association (R(2)=0.91 at 30°; R(2)=0.98 at 60°; and R(2)=0.97 at 90° knee angles; P<0.001). MMG peak-to-peak (MMG-PTP) and stimulation intensity were less well related (R(2)=0.63 at 30°; R(2)=0.67 at 60°; and R(2)=0.45 at 90° knee angles), although were still significantly associated (P≤0.006). Test-retest interclass correlation coefficients (ICC) for the dependent variables ranged from 0.82 to 0.97 for NMES-evoked torque, between 0.65 and 0.79 for MMG-RMS, and from 0.67 to 0.73 for MMG-PTP. Their standard error of measurements (SEM) ranged between 10.1% and 31.6% (of mean values) for torque, MMG-RMS and MMG-PTP. The MMG peak frequency (MMG-PF) of 30Hz approximated the stimulation frequency, indicating NMES-evoked motor unit firing rate. The results demonstrated knee angle differences in the MMG-RMS versus NMES-isometric torque relationship, but a similar torque related pattern for MMG-PF. These findings suggested that MMG was well associated with torque production, reliably tracking the motor unit recruitment pattern during NMES-evoked muscle contractions. The strong positive relationship between MMG signal and NMES-evoked torque production suggested that the MMG might be deployed as a direct proxy for muscle torque or fatigue measurement during leg exercise and functional movements in the SCI population.

Wet, volatile, and dry biomarkers of exercise-induced muscle fatigue

Background

The physiological background of exercise-induced muscle fatigue(EIMUF) is only poorly understood. Thus, monitoring of EIMUF by a single or multiple biomarkers(BMs) is under debate.

After a systematic literature review 91 papers were included.

Results

EIMUF is mainly due to depletion of substrates, increased oxidative stress, muscle membrane depolarisation following potassium depletion, muscle hyperthermia, muscle damage, impaired oxygen supply to the muscle, activation of an inflammatory response, or impaired calcium-handling. Dehydration, hyperammonemia, mitochondrial biogenesis, and genetic responses are also discussed. Since EIMUF is dependent on age, sex, degree of fatigue, type, intensity, and duration of exercise, energy supply during exercise, climate, training status (physical fitness), and health status, BMs currently available for monitoring EIMUF have limited reliability. Generally, wet, volatile, and dry BMs are differentiated. Among dry BMs of EIMUF the most promising include power output measures, electrophysiological measures, cardiologic measures, and questionnaires. Among wet BMs of EIMUF those most applicable include markers of ATP-metabolism, of oxidative stress, muscle damage, and inflammation. VO₂-kinetics are used as a volatile BM.

Conclusions

Though the physiology of EIMUF remains to be fully elucidated, some promising BMs have been recently introduced, which together with other BMs, could be useful in monitoring EIMUF. The combination of biomarkers seems to be more efficient than a single biomarker to monitor EIMUF. However, it is essential that efficacy, reliability, and applicability of each BM candidate is validated in appropriate studies.

Electromechanical delay components during relaxation after voluntary contraction: reliability and effects of fatigue

INTRODUCTION

Fatigue effects on total relaxation delay (R-DelayTOT ) components and measurement reliability were investigated.

METHODS

Electromyogram (EMG), force (F), and mechanomyogram (MMG) were recorded during maximum voluntary contraction from the biceps brachii muscle before and after fatigue. The delays between EMG cessation and onset of F decay (R-EMD), between F decay and onset of MMG largest displacement (MMG p-p) (R-Δt F-MMG), from the beginning to the end of MMG p-p (R-Δt MMGp-p ), and from the end of MMG p-p to F cessation (R-Δt MMG-Fend ) were calculated.

RESULTS

R-DelayTOT lasted 366 ± 10 ms. R-EMD, R-Δt F-MMG, R-Δt MMGp-p , and R-Δt MMG-Fend accounted for 6%, 8%, 59%, and 27% of R-DelayTOT , respectively. After fatigue, R-DelayTOT , R-EMD, R-Δt F-MMG, and R-Δt MMGp-p increased by 38%, 22%, 40%, 40%, and 38%, respectively (P<0.05). Reliability was very high (0.853-0.960).

CONCLUSIONS

R-Δt MMGp-p was the main contributor to R-DelayTOT . Fatigue affected all R-DelayTOT contributors, with a smaller effect on R-EMD.

Stretch-induced changes in tension generation process and stiffness are not accompanied by alterations in muscle architecture of the middle and distal portions of the two gastrocnemii

The study aimed to evaluate the stretch-induced changes in muscle architecture in different portions of the gastrocnemius medialis (GM) and lateralis (GL) muscles. The reliability and sensitivity of the measurements were also assessed. Fascicle length (FL) and pennation angle (PA) were calculated in the middle and distal portions of GM and GL at 0°, 10° and 20° of ankle dorsiflexion. At the same angles, passive torque (Tpass), peak torque (pT) and myotendinous junction displacement of GM were determined. Stiffness was calculated at muscle-tendon unit (MTU), muscle and tendon level. After static stretching administration, Tpass, pT and MTU stiffness decreased by 22%, 12% and 16%, respectively (p<0.05). Muscle and tendon stiffness decreased by 15% and 16% (p<0.05). Nevertheless, no changes in FL and PA occurred. The reliability of the approach was always very high (intraclass correlation coefficient>0.90), with an adequate level of sensitivity. pT after static stretching was related to decreases in MTU, muscle and tendon stiffness, but not to alterations in muscle architecture.

Mechanomyographic parameter extraction methods: an appraisal for clinical applications

The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity.

Mechanomyography and muscle function assessment: a review of current state and prospects

Previous studies have explored to saturation the efficacy of the conventional signal (such as electromyogram) for muscle function assessment and found its clinical impact limited. Increasing demand for reliable muscle function assessment modalities continues to prompt further investigation into other complementary alternatives. Application of mechanomyographic signal to quantify muscle performance has been proposed due to its inherent mechanical nature and ability to assess muscle function non-invasively while preserving muscular neurophysiologic information. Mechanomyogram is gaining accelerated applications in evaluating the properties of muscle under voluntary and evoked muscle contraction with prospects in clinical practices. As a complementary modality and the mechanical counterpart to electromyogram; mechanomyogram has gained significant acceptance in analysis of isometric and dynamic muscle actions. Substantial studies have also documented the effectiveness of mechanomyographic signal to assess muscle performance but none involved comprehensive appraisal of the state of the art applications with highlights on the future prospect and potential integration into the clinical practices. Motivated by the dearth of such critical review, we assessed the literature to investigate its principle of acquisition, current applications, challenges and future directions. Based on our findings, the importance of rigorous scientific and clinical validation of the signal is highlighted. It is also evident that as a robust complement to electromyogram, mechanomyographic signal may possess unprecedented potentials and further investigation will be enlightening.