Dataset Information

Predicting fatigue using countermovement jump force-time signatures: PCA can distinguish neuromuscular versus metabolic fatigue.

ABSTRACT:

Purpose

This study investigated the relationship between the ground reaction force-time profile of a countermovement jump (CMJ) and fatigue, specifically focusing on predicting the onset of neuromuscular versus metabolic fatigue using the CMJ.

Method

Ten recreational athletes performed 5 CMJs at time points prior to, immediately following, and at 0.5, 1, 3, 6, 24 and 48 h after training, which comprised repeated sprint sessions of low, moderate, or high workloads. Features of the concentric portion of the CMJ force-time signature at the measurement time points were analysed using Principal Components Analysis (PCA) and functional PCA (fPCA) to better understand fatigue onset given training workload. In addition, Linear Mixed Effects (LME) models were developed to predict the onset of fatigue.

Results

The first two Principal Components (PCs) using PCA explained 68% of the variation in CMJ features, capturing variation between athletes through weighted combinations of force, concentric time and power. The next two PCs explained 9.9% of the variation and revealed fatigue effects between 6 to 48 h after training for PC3, and contrasting neuromuscular and metabolic fatigue effects in PC4. fPCA supported these findings and further revealed contrasts between metabolic and neuromuscular fatigue effects in the first and second half of the force-time curve in PC3, and a double peak effect in PC4. Subsequently, CMJ measurements up to 0.5 h after training were used to predict relative peak CMJ force, with mean squared errors of 0.013 and 0.015 at 6 and 48 h corresponding to metabolic and neuromuscular fatigue.

Conclusion

The CMJ was found to provide a strong predictor of neuromuscular and metabolic fatigue, after accounting for force, concentric time and power. This method can be used to assist coaches to individualise future training based on CMJ response to the immediate session.

SUBMITTER: Wu PP

PROVIDER: S-EPMC6619745 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Predicting fatigue using countermovement jump force-time signatures: PCA can distinguish neuromuscular versus metabolic fatigue.

Wu Paul Pao-Yen PP Sterkenburg Nicholas N Everett Kirsten K Chapman Dale W DW White Nicole N Mengersen Kerrie K

PloS one 20190710 7

<h4>Purpose</h4>This study investigated the relationship between the ground reaction force-time profile of a countermovement jump (CMJ) and fatigue, specifically focusing on predicting the onset of neuromuscular versus metabolic fatigue using the CMJ.<h4>Method</h4>Ten recreational athletes performed 5 CMJs at time points prior to, immediately following, and at 0.5, 1, 3, 6, 24 and 48 h after training, which comprised repeated sprint sessions of low, moderate, or high workloads. Features of the ...[more]

PMID: 31291303

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Project description:The aim of this study was to identify the acute effects of a differential-learning training program on football kicking performance and countermovement jump. Twenty youth Portuguese under-15 football players participated in this study. All players were exposed to two training approaches: i) traditional, in which the players performed a total of 36 kicks in a blocked and repetitive approach; and ii) differential learning, which consisted in the 36 kicks using differential variations in each kick. Football kicking impact and velocity were assessed using a Stalker radar gun, while the kicking accuracy was assessed by aggregating the total number of points achieved during 12 kicks into a goal, which was divided into quantifiable scoring zones. Lastly, leg power was measured using a countermovement jump. Measurements were performed at baseline, post-intervention, and following a 35-minute training match. The comparisons between the baseline and post-test revealed that the differential learning approach promoted a possibly ~5% increase in the countermovement jump (small effects) and a likely ~3% increase in the average velocity (small effects) when compared with the traditional training approach. From the accuracy perspective, there was a moderate decrease from the baseline to the post-test and post-match in accurate kicks into zone 1 (centre of the goal) and a moderate decrease from the baseline to the post-match in accurate kicks into zone 5 (lateral zones at short height) in the differential intervention. In turn, a small increase in the accurate kicks into zones 4 and 6 (lateral zones of the goal and nearest to the bar, respectively) was found from the baseline to the post-match in the differential intervention. Overall, the differential learning intervention was more beneficial than a traditional training protocol with respect to acute improvements in countermovement jump performance, football kicking velocity and higher scoring zones kicking accuracy.

Project description:CONTEXT:? Despite an increase in the literature, few definitive guidelines are available to determine when an athlete has been fully rehabilitated after anterior cruciate ligament reconstruction (ACLR). OBJECTIVE:? To examine countermovement jump and isokinetic dynamometry measures to (1) identify which measures can best distinguish between ACLR and control participants and (2) provide normative values for identified measures in young adult male multidirectional field-sport athletes. DESIGN:? Cross-sectional study. SETTING:? Orthopaedic hospital. PATIENTS OR OTHER PARTICIPANTS:? Young adult male multidirectional field-sport athletes (n = 118) who had undergone unilateral patellar-tendon graft ACLR at least 6 months earlier and healthy male participants (n = 44) with no previous knee injury. INTERVENTION(S):? Single-legged countermovement jump (SL CMJ). MAIN OUTCOME MEASURE(S):? Three-dimensional biomechanical analysis of the SL CMJ and mean peak concentric knee-extension and -flexion torque using isokinetic dynamometry (ISO) were compared in the 2 groups. A stepwise logistic regression was carried out to identify the best predictors of ACLR- or control-group membership (SL CMJ height, limb symmetry index, peak power, joint power contribution, ISO peak torque, limb symmetry index variables). RESULTS:? The control group differed strongly from the ACLR group in isokinetic knee-extension peak torque (d = -1.33), SL CMJ performance (d > 0.4), and limb symmetry measures in both ISO and jump outcomes (d > 1.1). The combination of measures from both ISO and SL CMJ identified group membership with an accuracy of 89%. CONCLUSIONS:? Rehabilitation of ACLR patients may be complete when they achieve isokinetic knee-extension peak torque of 260% (±40%) body mass, SL CMJ performance of >17 cm (±4 cm), and reach-limb symmetry measures of >90% in both strength and jump outcomes. The outcomes in the control group can inform return-to-play criteria for young adult male multidirectional field-sport athletes after ACLR.

Dataset Information

Predicting fatigue using countermovement jump force-time signatures: PCA can distinguish neuromuscular versus metabolic fatigue.

Purpose

Method

Results

Conclusion

Publications

Predicting fatigue using countermovement jump force-time signatures: PCA can distinguish neuromuscular versus metabolic fatigue.

Similar Datasets

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