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In the context of back pain, great emphasis has been placed on the importance of trunk stability, especially in situations requiring compensation of repetitive, intense loading induced during high-performance activities, e.g., jumping or landing. This study aims to evaluate trunk muscle activity during drop jump in adolescent athletes with back pain (BP) compared to athletes without back pain (NBP). Eleven adolescent athletes suffering back pain (BP: m/f: n = 4/7; 15.9 +/- 1.3 y; 176 +/- 11 cm; 68 +/- 11 kg; 12.4 +/- 10.5 h/we training) and 11 matched athletes without back pain (NBP: m/f: n = 4/7; 15.5 +/- 1.3 y; 174 +/- 7 cm; 67 +/- 8 kg; 14.9 +/- 9.5 h/we training) were evaluated. Subjects conducted 3 drop jumps onto a force plate (ground reaction force). Bilateral 12-lead SEMG (surface Electromyography) was applied to assess trunk muscle activity. Ground contact time [ms], maximum vertical jump force [N], jump time [ms] and the jump performance index [m/s] were calculated for drop jumps. SEMG amplitudes (RMS: root mean square [%]) for all 12 single muscles were normalized toMIVC (maximum isometric voluntary contraction) and analyzed in 4 time windows (100 ms pre- and 200 ms post-initial ground contact, 100 ms pre- and 200 ms post-landing) as outcome variables. In addition, muscles were grouped and analyzed in ventral and dorsal muscles, as well as straight and transverse trunk muscles. Drop jump ground reaction force variables did not differ between NBP and BP (p > 0.05). Mm obliquus externus and internus abdominis presented higher SEMG amplitudes (1.3-1.9-fold) for BP (p < 0.05). Mm rectus abdominis, erector spinae thoracic/lumbar and latissimus dorsi did not differ (p > 0.05). The muscle group analysis over the whole jumping cycle showed statistically significantly higher SEMG amplitudes for BP in the ventral (p = 0.031) and transverse muscles (p = 0.020) compared to NBP. Higher activity of transverse, but not straight, trunk muscles might indicate a specific compensation strategy to support trunk stability in athletes with back pain during drop jumps. Therefore, exercises favoring the transverse trunk muscles could be recommended for back pain treatment.
Mueller, J, Mueller, S, Stoll, J, Baur, H, and Mayer, F. Trunk extensor and flexor strength capacity in healthy young elite athletes aged 11-15 years. J Strength Cond Res 28(5): 1328-1334, 2014-Differences in trunk strength capacity because of gender and sports are well documented in adults. In contrast, data concerning young athletes are sparse. The purpose of this study was to assess the maximum trunk strength of adolescent athletes and to investigate differences between genders and age groups. A total of 520 young athletes were recruited. Finally, 377 (n = 233/144 M/F; 13 +/- 1 years; 1.62 +/- 0.11 m height; 51 +/- 12 kg mass; training: 4.5 +/- 2.6 years; training sessions/week: 4.3 +/- 3.0; various sports) young athletes were included in the final data analysis. Furthermore, 5 age groups were differentiated (age groups: 11, 12, 13, 14, and 15 years; n = 90, 150, 42, 43, and 52, respectively). Maximum strength of trunk flexors (Flex) and extensors (Ext) was assessed in all subjects during isokinetic concentric measurements (60 degrees center dot s(-1); 5 repetitions; range of motion: 55 degrees). Maximum strength was characterized by absolute peak torque (Flex(abs), Ext(abs); N center dot m), peak torque normalized to body weight (Flex(norm), Ext(norm); N center dot m center dot kg(-1) BW), and Flex(abs)/Ext(abs) ratio (RKquot). Descriptive data analysis (mean +/- SD) was completed, followed by analysis of variance (alpha = 0.05; post hoc test [Tukey-Kramer]). Mean maximum strength for all athletes was 97 +/- 34 N center dot m in Flex(abs) and 140 +/- 50 N center dot m in Ext(abs) (Flex(norm) = 1.9 +/- 0.3 N center dot m center dot kg(-1) BW, Ext(norm) = 2.8 +/- 0.6 N center dot m center dot kg(-1) BW). Males showed statistically significant higher absolute and normalized values compared with females (p < 0.001). Flex(abs) and Ext(abs) rose with increasing age almost 2-fold for males and females (Flex(abs), Ext(abs): p < 0.001). Flex(norm) and Ext(norm) increased with age for males (p < 0.001), however, not for females (Flex(norm): p = 0.26; Ext(norm): p = 0.20). RKquot (mean +/- SD: 0.71 +/- 0.16) did not reveal any differences regarding age (p = 0.87) or gender (p = 0.43). In adolescent athletes, maximum trunk strength must be discussed in a gender- and age-specific context. The Flex(abs)/Ext(abs) ratio revealed extensor dominance, which seems to be independent of age and gender. The values assessed may serve as a basis to evaluate and discuss trunk strength in athletes.
Coordination of the trunk and hips is crucial for successful dynamic balance in many activities of daily living. Persons with recurrent low back pain (rLBP), both while symptomatic and during periods of symptom remission, exhibit dysfunctional muscle activation patterns and coordination of these joints. In a novel dynamic balance task where persons in remission from rLBP exhibit dissociated trunk motion, it is unknown how trunk and hip musculature are coordinated. Activation of hip and trunk muscles were acquired from nineteen persons with and without rLBP during the Balance-Dexterity Task, which involves balancing on one limb while compressing an unstable spring with the other. There were no between-group differences in activation amplitude for any muscle groups tested. In back-healthy control participants, hip and trunk muscle activation amplitudes increased proportionally in response to the added instability of the spring (R = 0.837, p < 0.001). Increases in muscle activation amplitudes in the group in remission from rLBP were not proportional (R = 0.113, p = 0.655). Instead, hip muscle activation in this group was associated with task performance, i.e. dexterous control of the spring (R = 0.676, p = 0.002). These findings highlight atypical coordination of hip and trunk musculature potentially related to task demands in persons with rLBP even during remission from pain.
TRIPOD
(2021)
Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data.
Background and Objectives: Low back pain is a worldwide health problem. An early diagnosis is required to develop personalized treatment strategies. The Risk Stratification Index (RSI) was developed to serve the purpose. The aim of this pilot study is to cross-culturally translate the RSI to a French version (RSI-F) and evaluate the test-retest reliability of RSI-F using a French active population. Materials and Methods: The RSI was translated from German to French (RSI-F) based on the guidelines of cross-cultural adaptation of self-report measures. A total of 42 French recreational athletes (age 18–63 years) with non-specific low back pain were recruited and filled in the RSI-F twice. The test-retest reliability was examined using intraclass correlation coefficient (ICC1,2) and Pearson correlation coefficient. Results: Finally, 33 questionnaires were analyzed (14 males and 19 females, age 31 ± 10 years, 9.5 ± 3.2 h/week of training). The test-retest of RSI-F CPI and DISS were excellent (CPI: ICC1,2 = 0.989, p < 0.001; r = 0.989, p < 0.001; DISS: ICC1,2 = 0.991, p < 0.001; r = 0.991, p < 0.001), as well as Korff pain intensity (ICC1,2 = 0.995, p < 0.001; r = 0.995, p < 0.001) and disability (ICC1,2 = 0.998, p < 0.001; r = 0.998, p < 0.001). Conclusion: The RSI-F is linguistically accurate and reliable for use by a French-speaking active population with non-specific low back pain. The RSI-F is considered a tool to examine the evolution of psychosocial factors and therefore the risk of chronicity and the prognostic of pain. Further evaluations, such as internal, external validity, and responsiveness should be evaluated in a larger population.
A new method is proposed for tracking individual motor units (MUs) across multiple experimental sessions on different days. The technique is based on a novel decomposition approach for high-density surface electromyography and was tested with two experimental studies for reliability and sensitivity. Experiment I (reliability): ten participants performed isometric knee extensions at 10, 30, 50 and 70% of their maximum voluntary contraction (MVC) force in three sessions, each separated by 1 week. Experiment II (sensitivity): seven participants performed 2 weeks of endurance training (cycling) and were tested pre-post intervention during isometric knee extensions at 10 and 30% MVC. The reliability (Experiment I) and sensitivity (Experiment II) of the measured MU properties were compared for the MUs tracked across sessions, with respect to all MUs identified in each session. In Experiment I, on average 38.3% and 40.1% of the identified MUs could be tracked across two sessions (1 and 2 weeks apart), for the vastus medialis and vastus lateralis, respectively. Moreover, the properties of the tracked MUs were more reliable across sessions than those of the full set of identified MUs (intra-class correlation coefficients ranged between 0.63-0.99 and 0.39-0.95, respectively). In Experiment II, similar to 40% of the MUs could be tracked before and after the training intervention and training-induced changes in MU conduction velocity had an effect size of 2.1 (tracked MUs) and 1.5 (group of all identified motor units). These results show the possibility of monitoring MU properties longitudinally to document the effect of interventions or the progression of neuromuscular disorders.
Coaches and athletes in elite sports are constantly seeking to use innovative and advanced training strategies to efficiently improve strength/power performance in already highly-trained individuals. In this regard, high-intensity conditioning contractions have become a popular means to induce acute improvements primarily in muscle contractile properties, which are supposed to translate to subsequent power performances. This performance-enhancing physiological mechanism has previously been called postactivation potentiation (PAP). However, in contrast to the traditional mechanistic understanding of PAP that is based on electrically-evoked twitch properties, an increasing number of studies used the term PAP while referring to acute performance enhancements, even if physiological measures of PAP were not directly assessed. In this current opinion article, we compare the two main approaches (i.e., mechanistic vs. performance) used in the literature to describe PAP effects. We additionally discuss potential misconceptions in the general use of the term PAP. Studies showed that mechanistic and performance-related PAP approaches have different characteristics in terms of the applied research field (basic vs. applied), effective conditioning contractions (e.g., stimulated vs. voluntary), verification (lab-based vs. field tests), effects (twitch peak force vs. maximal voluntary strength), occurrence (consistent vs. inconsistent), and time course (largest effect immediately after vs. similar to 7 min after the conditioning contraction). Moreover, cross-sectional studies revealed inconsistent and trivial-to-large-sized associations between selected measures of mechanistic (e.g., twitch peak force) vs. performance-related PAP approaches (e.g., jump height). In an attempt to avoid misconceptions related to the two different PAP approaches, we propose to use two different terms. Postactivation potentiation should only be used to indicate the increase in muscular force/torque production during an electrically-evoked twitch. In contrast, postactivation performance enhancement (PAPE) should be used to refer to the enhancement of measures of maximal strength, power, and speed following conditioning contractions. The implementation of this terminology would help to better differentiate between mechanistic and performance-related PAP approaches. This is important from a physiological point of view, but also when it comes to aggregating findings from PAP studies, e.g., in the form of meta-analyses, and translating these findings to the field of strength and conditioning.
We are glad to introduce the Second Journal Club of Volume Five, Second Issue. This edition is focused on relevant studies published in the last few years in the field of resistance training, chosen by our Editorial Board members and their colleagues. We hope to stimulate your curiosity in this field and to share with you the passion for the sport, seen also from the scientific point of view. The Editorial Board members wish you an inspiring lecture.