Tensiomyography Variable Trend of Changes After Acute Muscle Fatigue Induced by Acute Exercise: a Systematic Review and Meta-analysis

Abstract

Tensiomyography (TMG) has advantage in measuring fatigue. However, no studies have used a meta-analysis approach to analyze the trend of changes in TMG variables for acute muscle fatigue induced by an acute exercise. This study is the first systematic review and meta-analysis to establish criteria for measuring acute fatigue using TMG by quantifying trend of changes in TMG variables. Searches were conducted in Web of Science and Pubmed from December 6, 2020 to January 7, 2021. 16 studies were included that they used in TMG for measuring acute muscle fatigue that was caused by acute exercises in rectus femoris or biceps femoris. The meta-analysis results indicated that in the biceps femoris, showed a significant (p < .05) decrease in all TMG variables of the elite athletes. Also, in the overall effects of maximum displacement and mean velocity until 90% Dm (Vc90) showed significant (p < .05) decreasing trend. In the rectus femoris, showed a significant (p < .05) decreasing trend was found for maximum displacement (Dm) in the average person, while contraction time (Tc) showed a decreasing trend in elite athletes and overall. In conclusion, acute muscle fatigue was induced decreased Dm, Tc, Vc90 in the TMG measurement after an acute exercise. These results TMG could be used as a muscle fatigue indicator and help develop a more proper protocol for testing the response of body to muscle fatigue.

Introduction

Tensiomyography (TMG) is a mechanomyography method that non-invasively evaluates the mechanical properties of skeletal and neuromuscular muscles. It is used to measure the stiffness of a single muscle and neuromuscular muscle fatigue, especially after an acute exercise ^1,2,3. TMG induces mechanical contraction by stimulating the muscle with a single electric stimulation of 0–100 mA for 1 ms and then measures the response ⁴. TMG evaluates the maximum contraction displacement of the muscle (i.e., maximum displacement [Dm]), the time taken to contract from 10–90% of the maximum contraction displacement (i.e., the contraction time [Tc]), the time taken from the start of stimulation to 10% of the maximum contraction displacement (i.e., the delay time [Td]), the time from 50% of the maximum contraction displacement to 50% of the descending curve (i.e., the sustain time [Ts]), and the time taken from 90–50% of the maximum contraction displacement in the descending curve (i.e., the relaxation time [Tr]). Measurement-remeasurement and intra-evaluator reliability indices are assessed as Poor (< 0.5), Moderate (0.5 to < 0.75), Good (0.75 to < 0.9), and Excellent (≥ 0.9) based on the 95% confidence interval (CI) of the intraclass correlation coefficient (ICC). Dm (0.91–0.99) and Tc (0.70–0.98) are the most reliable TMG variables in repeated measurements ^5,6. However, Tc can be affected by the Dm size as Tc represents the time taken to reach 90% of Dm. Therefore, the normalized response speed (Vrn), radial displacement velocity (Vrd), the mean velocity until 10% Dm (Vc10), and the mean velocity until 90% Dm (Vc90) compensate for this when calculating muscle contraction speed ^2,4,7.

Running, jumping, and turning movements common in sports occur in the lower body. During running, the knee flexors and extensors compensate for the gastrocnemius activity decrease due to fatigue to maintain the stride pattern ⁸. In jumping motions, the hamstrings and quadriceps are elongated to store elastic energy and play an important role in exerting power ^9,10. As the hamstrings and quadriceps play an essential role in lower body movement, they are widely used in post-exercise fatigue measurements. However, fatigue measurement studies using TMG have also been conducted with the biceps femoris (BF) and rectus femoris (RF) ^4,11,12, but the criteria for measuring the degree of fatigue are ambiguous as these previous studies reported inconsistent results. Some reported decreased Dm due to increased muscle stiffness after the induction of fatigue ^{3,13,14,15,16}, while others reported increased Dm due to decreased muscle stiffness ^12,17. Additionally, BF and RF have different responses after the same movement owing to differences in each muscle’s role during the movement, which manifests as different responses ^4,13,18.

Although TMG has a potential advantage in measuring fatigue, but the result interpretation is ambiguous as the reported trend of changes in the literature are inconstant. However, no studies have used a meta-analysis approach to analyze the trend of changes in TMG variables for acute muscle fatigue induced by an acute exercise. This study aimed to establish criteria for measuring fatigue using TMG by quantifying trend of changes in TMG variables.

Methods

Literature Review

We performed a literature search, systematic research identification review, and meta-analysis using specific variables. The literature search focused on studies measuring muscle fatigue with TMG before and after an acute exercise to examine muscle condition changes after an acute exercise. The search engines used were PubMed and Web of Science, starting December 6, 2020, and ending January 7, 2021. The keywords were: (1) “Tensiomyography.” The literature inclusion criteria were: studies on TMG measurement before and after an acute exercise, RF or BF measurement studies, and studies on TMG measurement immediately after exercise fatigue. The exclusion criteria included unrelated literature, such as review papers, case studies, and animal studies. One researcher conducted the literature search. In total, 282 papers were initially identified, and 266 were excluded after reading the title and summary; 107 were duplicate studies, 11 were review papers, 32 were case studies, and 116 were unrelated subjects. Finally, 16 papers were included in the meta-analysis (Fig. 1)^{2,3,4,11,12,13,14,15,16,17,18,19,20,21,22,23}.

Tensiomyography

TMG was used to evaluate muscle fatigue induced by an acute exercise. The included studies evaluated the BF, RF, vastus lateralis (VL), vastus medialis (VM), semitendinosus (ST), and medial gastrocnemius (GM) muscles and the Dm, Tc, Td, Ts, Tr, Vrn, Vrd, Vc10 and Vc90 TMG measurement variables. For the analysis, Vrn was converted into Tc using the formula \(\text{V}\text{r}\text{n}=\frac{0.8}{\text{T}\text{c}}\) ²⁴. Vc90 was calculated using \(\text{V}\text{c}90=\frac{\text{D}\text{m} \text{*} 0.9}{\text{T}\text{c} + \text{T}\text{d}}\)to determine the muscle contraction velocity ⁷. All of the studies measured TMG before and immediately after exercise. The BF measurement was taken with the subject prone position on a wedge foam cushion with a 5–15° flexion in the knee joint. The RF measurement was taken with the subject supine position on a special triangular wedge foam cushion with the knee extension at 140–150° ²⁵. During the measurements, the electric potential was administered with an intensity of 0–100 mA for 1 ms and gradually increased until maximal Dm. There was at least a 10 s break between measurements ²⁶.

This study analyzed two muscles (BF and RF) and three TMG intervention variables (Dm, Tc, and Vc90). Muscle fatigue was induced by the exercise specified in each study ², the most measured muscles, and reliable TMG measurement variables were used for our analysis ⁶.

Acute Exercise

The following an acute exercises were used to induce fatigue: repeated sprint ability (RSA), maximal incremental cycling test (MICT), maximal voluntary isometric contraction (MVIC), weight training, running, swimming, forward-tucked somersaults, and surfing.

Meta-analytic approaches

All statistical data analyses were performed using Comprehensive Meta-Analysis software (version 3.0, Biostat Inc., USA). The individual and overall effect sizes (ES) were calculated using Hedges’ g with 95% CI ²⁷. Variable increases were labeled as positive, and decreases were labeled as negative. For example, a positive Hedges’ g value for Tc, Dm, and Vc90 indicated an increase in each variable after the exercise. For reliability, the ES of all values were calculated, and values more than twice the standard deviation were excluded through a moderate process ²⁸. Random-effects meta-analysis models were used, assuming that no common ES appeared in individual studies ²⁹. ES was evaluated as Very Small (< 0.2), Small (0.2 to < 0.6), Average (0.6 to < 1.2), Large (1.2 to < 2.0), and Very Large (≥ 2.0) ³⁰. All meta-analysis results are shown in figure by forest plot.

The Higgins and Green I² test was used to identify the level of heterogeneity in the literature, and an I² value of 50% or higher was considered heterogeneous ³¹. The methods used for the literature bias test were: (1) the original funnel plot was compared with a revised funnel plot after applying the trim-and-fill technique ³², and (2) the Egger’s regression test was based on the null hypothesis that symmetry exists in the funnel plot. Thus, a P-value for the intercept (β0) < 0.05 indicated a violation of the symmetry assumption, representing a high publication bias ³³.

Finally, the critical appraisal tool (CAT) scale was used to estimate the methodology quality ³⁴. The CAT consists of 13 questions with five items on the study validity and reliability, four items only on the study validity, and four items only on the reliability (Table 1).

The answers to the questions are either yes, no, or not applicable, with 1 point for yes and 0 points for no. As CAT does not provide an overall quality score, the evaluation method by was modified so that the methodological quality could be evaluated ³⁵. A score of 8 points or higher indicated a low risk of bias and excellent methodological quality, 7 points indicated a moderate risk of bias and average methodological quality, and 6 or fewer points indicated a high risk of bias and low methodological quality. Three researchers conducted independent assessments for quality assessment and derived the final score after a discussion.

Results

Caption RSA repeated sprint ability, MVIC maximal voluntary isometric contraction BF biceps femoris, RF rectus femoris, VL vastus lateralis, VM vastus medialis, ST semitendinosus, GM medial gastrocnemius Dm maximum displacement, Tc contraction time, Td delay time, Ts sustain time, Tr relaxation time, Vrd radial displacement velocity, Vrn normalized response speed, Vc10 mean velocity until 10% Dm, Vc90 mean velocity until 90% Dm

Tensiomyography

All 16 studies analyzed RF, 13 studies measured BF, 6 measured VL, 5 measured VM, 1 measured ST, and 2 measured GM. Regarding TMG variables, 14 studies measured Dm, 13 measured Tc, 9 measured Td, 3 measured Vc90, 1 measured Vc10, 5 measured Ts, 4 measured Tr, 3 measured Vrn, and 1 measured Vrd. Papers that presented Dm, Tc, and Td together used the Vc90 calculation formula to convert them into Vc90 (Table 2).

Exercise Protocols

Of the 16 studies, 4 used RSA, 1 used MICT, 1 used MVIC, 3 used weight training, 3 used running, 1 used swimming, 2 used forward-tucked somersaults, and 1 used surfing to induce acute muscle fatigue (Table 2).

Methodological Bias Assessment

The mean CAT score and SD was 9.5 ± 1.5 (range 6–11), 14 papers had a low risk of bias and good methodological quality, 1 had a moderate risk of bias and average methodological quality, and 1 had a high risk of bias and low methodological quality (Table 3).

The random effects meta-analysis model analyzed the differences in the TMG variables that measured BF and RF muscle fatigue after an acute exercise.

The ES of BF Dm was insignificant for the average person (Hedges’s g = 0.007, 95% CI = -0.189 to 0.202, p = 0.946, I² = 0.00%), whereas the elite athletes showed a small but significant decrease (Hedges’s g = -0.386, 95% CI = -0.566 to -0.207, p = 0.000, I² = 9.50%). The overall effect also showed a small but significant decrease (Hedges’s g = -0.207, 95% CI = -0.339 to -0.075, p = 0.002, I² = 24.51%). And the ES of RF Dm showed a small but significant decrease for the average person (Hedges’s g = -0.298, 95% CI = -0.518 to -0.078, p = 0.008, I² = 34.94%), whereas the change was insignificant in elite athletes (Hedges’s g = 0.132, 95% CI = -0.101 to 0.366, p = 0.266, I² = 55.47%). The overall effect was statistically insignificant (Hedges’s g = -0.095, 95% CI = -0.256 to 0.065, p = 0.242, I² = 52.67%) (Fig. 2).

The ES of BF Tc change was insignificant in the average person (Hedges’s g = 0.014, 95% CI = -0.180 to 0.209, p = 0.885, I² = 0.00%), but showed a very small but significant decrease in elite athletes (Hedges’s g = -0.164, 95% CI = -0.316 to -0.013, p = 0.033, I² = 0.00%). However, the overall effect was statistically insignificant (Hedges’s g = -0.097, 95% CI = -0.216 to 0.022, p = 0.111, I² = 0.00%). And the ES of RF Tc change was insignificant in the average person (Hedges’s g = -0.144, 95% CI = -0.304 to 0.016, p = 0.078, I² = 0.00%), yet showed a very small but significant decrease in elite athlete (Hedges’s g = -0.172, 95% CI = -0.336 to -0.007, p = 0.041, I² = 8.51%). The overall effect also showed a very small but significant decrease (Hedges’s g = -0.157, 95% CI = -0.272 to -0.043, p = 0.007, I² = 0.00%) (Fig. 3).

The ES of BF Vc90 change was insignificant in the average person (Hedges’s g = -0.159, 95% CI = -0.498 to 0.181, p = 0.359, I² = 15.20%), but showed a small but significant decrease in elite athletes (Hedges’s g = -0.387, 95% CI = -0.663 to -0.111, p = 0.006, I² = 60.71%). The overall effect also showed a small but significant decrease (Hedges’s g = -0.296, 95% CI = -0.510 to -0.082, p = 0.007, I² = 55.15%). And the ES of RF Vc90 change was insignificant for the average person (Hedges’s g = 0.335, 95% CI = -0.295 to 0.965, p = 0.298, I² = 85.01%), elite athletes (Hedges’s g = 0.115, 95% CI = -0.253 to 0.484, p = 0.540, I² = 80.11%), and in the overall effect (Hedges’s g = 0.171, 95% CI = -0.147 to 0.489, p = 0.292, I² = 82.28%) (Fig. 4).

Thus, in BF a substantial decreasing trend in all variables was observed in the elite athletes, with a substantial decreasing trend in the overall effects of Dm and Vc90. Whereas, in RF a substantial decreasing trend was found for Tc in the elite athletes, while Dm was substantial decreasing trend in the average person.

Discussion

This study is the first to conduct a systematic literature review and meta-analysis on TMG variable trend of changes when measuring acute muscle fatigue induced by an acute exercise using a large sample number obtained from the literature. The CAT evaluation showed that the bias risk and the methodological level were excellent. Further, the meta-analysis results confirmed a specific trend of changes when measuring acute muscle fatigue induced by an acute exercise with TMG, and the trend of changes were different for BF and RF.

The literature analysis demonstrated a substantial decrease in the overall effect in BF Dm and Vc90 and RF Tc. The ES of BF Dm was Hedges’s g = -0.207, the ES of BF Vc90 was Hedges’s g = -0.296, and the ES of RF Tc was Hedges’s g = -0.157. Elite athletes showed a substantial decrease in all BF variables and RF Tc after an acute exercise. The ES was Hedges’s g = -0.386 for BF Dm, Hedges’s g = -0.164 for BF Tc, Hedges’s g = -0.387 for BF Vc90, and Hedges’s g = -0.172 for RF Tc. Conversely, in the average person only the RF Dm showed a substantial decrease, and the ES of RF Dm was Hedges’s g = -0.298.

Regarding the overall ES, there was a substantial decrease in the BF Vc90, which is consistent with the results of a study that reported a decrease in Vc90 after an acute exercise ^2,22. This result is owing to the pH inside the muscle fibers, which decreases due to acute muscle fatigue, reducing the transmission rate of the action potential and affecting the contraction force and contraction rate. A decrease in the number of adenosine triphosphates may cause a decrease in the contractile force by reducing actin-myosin cross-bridge. Additionally, the ratio of fast-twitch muscle fibers (Type II) in the quadriceps and hamstrings is higher than slow-twitch muscle fibers (Type I). Type II muscle fibers have fewer mitochondria and less oxidative metabolism for energy production than Type I, resulting in low fatigue resistance, potentially leading to a contraction rate decrease by becoming fatigued first during exercise ^{36,37,38,39,40}. Furthermore, there was a substantial decreasing trend of changes in Dm, which is consistent with previous results reporting that muscle fatigue after an exercise increases tension and stiffness ^{3,13,15,16,21}.

That study reported that muscle fatigue causes a decrease in pH from accumulating H⁺ and Pi in the muscle fiber, thereby increasing Ca²⁺, which reduces the sensitivity of troponin to Ca²⁺ and inhibits reabsorption in the sarcoplasmic reticulum. Ultimately, stiffness increases as a result of a reduced actin-myosin bond separation rate ^38,40. This phenomenon can be thought of as a way to store more energy generated during exercise by increasing muscle stiffness instead of decreasing muscle activity when muscle fatigue increases ⁴¹.

RF only showed a substantial decreasing trend for Tc, likely explained by the fact that the acute exercise used in each study did not cause substantial muscle fatigue. Several studies included in the analysis reported that the exercise was not enough to induce fatigue in RF ^20,23, and reported an improvement in the movement response time due to the post-exercise post-activation potentiation (PAP), which can induce a Tc reduction. Additionally, although not substantial, the RF Vc90 slightly increased, which was affected by the inclusion of some studies that reported such results ²².

There was a difference in the fatigue measurement results between the average person and elite athletes. The average person only showed a substantial decrease in the RF Dm, whereas elite athletes showed a substantial decrease in the all BF variables and RF Tc. This difference is thought to be because the acute exercise used in the literature had many movements requiring explosive muscle strength where hamstring activity is very important, such as running and jumping ⁴². The degree of fatigue could have also been affected by the difference in the level of muscular activation during exercise, as there are differences between an average person and an elite athlete in their performance ability and training level, as demonstrated by previous studies ^43,44,45. Previous studies detailed that a higher training level shows a faster and stronger expression of muscular strength and greater activity ^46,47,48. Therefore, the athletes likely generated a greater force in the hamstrings during the exercise compared to the average person, perhaps resulting in a higher fatigue level after exercise ^46,47,49. The quadriceps assist with knee stability during exercise, and during explosive movements, it creates motion in coordination with the hip extensor muscle ^50,51,52. In the acute exercise used in these studies, RF performs this role and is thought to explain the decrease in Tc and Dm in elite athletes and average persons.

This analysis had some limitations. The number of papers was small because research using TMG is relatively new. Further, the muscle fatigue response induced by acute exercise was reported differently in each study ^3,53. Therefore, to identify trend of changes, more studies measuring acute muscle fatigue induced by acute exercise are required. Furthermore, the exercises used in the studies are multiple joint exercise, which could have been inappropriate for inducing localized fatigue ^54,55. Thus, it is necessary to use an exercise that induces fatigue exactly at the measurement site ^52,56,57, and additional research should verify whether the exercise, the amount, and the intensity are sufficient. Further, a study that reported the PAP response due to multiple joint exercise was also included in our analysis. However, PAP wasn't clear how it works so continual research on exercise and PAP response is also necessary ^58,59. Lastly, there was only one researcher who collected papers, and only English publications were considered for this study, potentially causing unintentional sampling bias.

Conclusions

Our study results indicate that acute muscle fatigue was induced if Dm, Tc, and Vc90 decreased in TMG measurement after an acute exercise. These results could be used as a muscle fatigue indicator when attempting to induce fatigue through exercise, which could help develop a more suitable protocol for testing the body’s response to muscle fatigue. Athletes could also check their fatigue level after exercise by checking for decreases in Dm, Tc, and Vc90 in the BF after a complex lower body movement, which could help optimize exercise programs.

Declarations

Conflict of interest

The authors report no conflict of interest.

Acknowledgements

None.

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