Effects of Fatigue on Lower Limb Biomechanics and Kinetic Stabilization During the Tuck-Jump Assessment

Noncontact, single-legged landings with knee-abduction collapse is one of the most common mechanisms of anterior cruciate ligament (ACL) injury in multidirectional female sports such as netball and soccer.^1,2 The risk of such landing strategies is postulated to be exacerbated by fatigue, despite inconsistent alterations in lower limb biomechanics being observed.^3,4 The most consistent fatigue-induced biomechanical alterations occur in the sagittal plane, with knee and hip flexion decreasing at initial contact and increasing at their peaks.^5–7 This kinematic strategy may be indicative of a stiffer landing strategy at initial contact and is commonly associated with ACL injury, especially in female athletes. Stiff landings can place excessive loads on the knee joint, predisposing athletes to a greater risk of ACL injury.⁸

Methodological considerations are crucial in the development of fatigue-related research. Recent literature highlights no clear difference in the effect of central versus peripheral fatigue protocols, with many researchers implementing laboratory test protocols with tasks including only vertical and sagittal-plane movements (eg, treadmill running, intermittent shuttle runs, squats, repetitive jumping protocols, or repetitive isolated hip and knee movements).^3,7 Variations in outcome measures and task selection may be responsible for the inconsistently reported alterations in biomechanical variables in response to fatigue, with researchers reporting variations of single- or double-legged jump-landing tasks in either the frontal or the sagittal plane.^3,7Uniplanar activity (eg, drop vertical jump) may not be sensitive enough to detect the true effects of fatigue on the neuromuscular system and may neglect the complex interaction of physical and cognitive fatigue on injury-risk variables.⁷ When athletes are in a fatigued state, a sudden perturbation or unanticipated stimulus of any component may be sufficient to provoke dynamic instability⁷ and expose athletes to injurious lower limb biomechanics, placing them at heightened risk of ACL injury. Furthermore, their ability to counteract these unanticipated perturbation stimuli might change dynamically depending on their susceptibility to fatigue, which may not be detectable in single-repetition tasks. One consideration, therefore, may be to implement a fatigue protocol that is both physically (central and peripheral) and cognitively challenging and includes multiple repetitions, which may have more ecological validity and thus more accurately reflect the multifactorial effects of fatigue.⁹

The tuck-jump assessment (TJA) is a repetitive rebounding task that exposes athletes to similar vertical forces regularly experienced during sporting actions.¹⁰ It requires athletes to perform maximal height tuck jumps for 10 seconds while attempting to satisfy specific technical requirements (eg, thighs reaching parallel, landing in the same footprint, and remaining facing forward). The cyclical nature of repeated tuck jumps and self-regulated jump heights cognitively challenges athletes and provides an indication of reactive strength capabilities during the assessment of acute fatigue and diminished feed-forward responses.¹¹ The TJA is typically used as a screening method to visually assess and subjectively rate athletes in a nonfatigued state. However, recently, researchers have reported a larger number of flaws and jumps performed during the test after an anaerobic fatigue protocol.¹² Although these findings are of interest, reliance on the traditional subjective scoring alone may not expose the underlying kinetics of functional change postfatigue. Authors have also attributed the postfatigue increase in number of jumps to a learned effect and increased motivation.¹² Alternatively, the postfatigue increase could be due to kinetic alterations changing the jumping strategy, which can only be quantified using more sensitive measures.

Kinetic analysis of the TJA has recently been reported with a specific focus on the stability and consistency of vertical ground reaction forces (VGRFs) during the repetitive rebounding task.¹³ Using a trial stabilization technique, researchers identified distinct variations in kinetic stabilization between participants, whereby some athletes stabilized within the first few jumping cycles of the TJA while others did not stabilize until much later. The authors indicated that early variation in kinetics could be indicative of a greater risk of injury, with athletes who stabilize earlier demonstrating fewer visual technical flaws during the assessment.¹³ Alterations in kinetics have been observed in female runners when fatigued and were attributed to changes in running cadence, step length, and lower extremity joint kinematics to minimize impact forces and protect against injury.¹⁴ Movement variability may also coincide with changes in kinetic stabilization, and these changes are likely to occur to varying degrees depending on athletes’ susceptibility or resistance to fatigue or their capacity to maintain performance under fatigued states. It is also possible that greater kinetic variation may be evident postfatigue, albeit with an absence of any kinematic changes. Kinetic analysis and stabilization could enhance the sensitivity of the visual 2-dimensional (2D) TJA and may provide a more relevant measure of the biomechanical responses associated with sports competition–related fatigue and ACL injury risk.

The purpose of our study was to examine the effects of a sport-specific fitness protocol on ACL injury risk by analyzing repeated tuck jumps using the visual 2D assessment in addition to VGRFs and kinetic stabilization in a cohort of healthy female athletes. The first hypothesis was that athletes would demonstrate a higher composite score due to more technical flaws and maladaptation in landing strategies when fatigued. The second hypothesis was that kinetic stabilization would be delayed during the testing period due to reduced neuromuscular control.

METHODS

Procedures

Familiarization

Participant anthropometrics were recorded before a standardized dynamic warm-up involving multidirectional jogging, dynamic stretching, bilateral and unilateral jumps, acceleration and deceleration exercises, and change-of-direction movements progressing in intensity of effort. The protocols for the TJA and SSFP were described and demonstrated to participants, who were then allowed to practice each protocol until they were deemed technically proficient by the principal investigator (L.S.K.). All participants then completed 5 maximal repetitions of the fatigue circuit, and the mean completion time over the 5 trials was used to individually dictate the work-to-rest (W:R) ratio for the SSFP, which was completed on the day of testing.

Fatigue Protocol

The SSFP was based on a netball-specific fitness test (Net-Test) designed by Mungovan et al which consists of 14 netball-specific movements performed around the markings of a netball court covering approximately 150 m.¹⁵ We used pilot testing to determine the number of repetitions and W:R ratio to elicit fatigue. Participants performed 20 repetitions (4 sets of 5 repetitions) of the Net-Test circuit, covering a total distance of 3000 m and working at a W:R of 1:2. To mimic the time between quarters in a netball match, we provided a 3-minute rest period at the end of each set. The total SSFP took approximately 50 to 60 minutes to complete, and oral encouragement was used throughout the SSFP to promote maximal effort.

Wireless single-beam timing gates (Smart Speed; Fusion Sport), positioned at the start and end of the circuit (see Figure 1 in Mungovan et al), were used to measure the time (in seconds) taken to complete each repetition of the circuit, and work and recovery times were measured using a commercially available tablet application (Seconds Interval Timer version 3.16.2; Runloop Ltd).¹⁵ We also monitored neuromuscular function and perceived markers of fatigue during the SSFP. Alterations in neuromuscular function were deduced from a submaximal, 2-legged hopping protocol on a contact mat; this protocol is a highly controlled method to assess the neuromuscular response to fatigue.^16,17 A single trial was recorded pre-SSFP and immediately after each set. Participants were asked to hop on 2 limbs in time with a digital, audible metronome (Metronome version 3.3.5; ONYX Apps) on the contact mat at a frequency of 2.5 Hz. Using measures of leg length and body mass, we calculated vertical relative lower extremity stiffness (k_leg), which can indicate compromised neuromuscular control in response to fatigue.^18–20 Internal physiological load was measured using heart rate (HR) chest monitors (model Rs800cx; Polar Electro Inc). Perceptual load was determined using ratings of perceived exertion (RPEs; Borg CR10 scale) for breathlessness (RPE-B) and leg exertion (RPE-L).²¹ An increase in the RPE value using the CR10 scale has been correlated with a reduction in maximal voluntary muscle force.²² Via pilot testing, we identified that the SSFP elicited a score of ≥9 for RPE-L and RPE-B, indicating that participants were at maximal fatigue or exhaustion on cessation of the protocol, with changes in k_leg observed from prefatigue to postfatigue (44.27 ± 7.25 BW·m⁻¹ to 37.46 ± 9.30 BW·m⁻¹; P = .003; Hedges g = 1.03). Maximal HR and RPE measures were collected immediately after the completion of each circuit repetition.

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Tuck-Jump Assessment

Participants performed a single set of the TJA before and after the SSFP. In accordance with previously published guidelines, they performed continuous maximal height tuck jumps for 10 seconds while adhering to the following instructions: (1) bring the knees up to hip height during each jump, (2) maintain the same footprint, and (3) remain facing forward during the test.^13,23 Two mounted iPads (Apple Inc; 1080p high definition at 60 frames per second), positioned 5 m away from the test area (determined by triangulation) and set at a height of 70 cm, were used to capture 2D frontal- and sagittal-plane data for retrospective scoring. The modified TJA scoring criteria were used to score each participant across the following 10 items: (1) knee valgus at landing, (2) thighs do not reach parallel, (3) thighs not equal side to side, (4) foot placement not shoulder width apart, (5) foot placement not parallel, (6) foot contact timing not equal, (7) excessive landing contact noise, (8) pause between jumps, (9) technique declines before 10 seconds, and (10) does not land in same footprint.¹⁰ If participants met the criterion, a score of zero was recorded. If participants did not meet a criterion ≥2 times, a score of 1 or 2 (magnitude of the score) was recorded for the respective category.¹⁰ The composite score was calculated as the total sum of the 10 criteria.

Ten-second trials of the TJA were performed on a single 900- × 600-mm ground-fixed force plate, sampling at 1000 Hz (Type 2812a; Kistler Instruments AG), with data captured over a 15-second period. Force-time data were instantaneously captured using the manufacturer’s software (Bioware version 5.1) and subsequently exported to Microsoft Excel (Microsoft Corp) and a customized MATLAB (R2018b; The MathWorks Inc) script. To ensure accuracy, we zeroed the force plate before each trial and filtered data using a recursive, fourth order, low-pass digital Butterworth filter with a cutoff frequency of 50 Hz determined by residual analysis. The force threshold criterion to identify the beginning of each jumping cycle (ie, initial contact) and the end of the ground contact phase was determined when the force exceeded 10 N.²⁴ Force data were normalized to body weight (BW) for statistical analyses. For each jumping cycle (not including the initial countermovement jump), 11 discrete kinetic variables were extracted and calculated using methods and definitions previously reported¹³ and are described in the Supplemental Table (available online at https://dx.doi.org/10.4085/1062-6050-0252.23.S1). Extracted variables included the following: time of jump cycle (seconds), ground contact time (GCT; seconds), flight time (FT; seconds), duty factor (DF) ratio, jump height (meters), peak VGRF (BW), peak center-of-mass (COM) displacement (meters), k_leg (BW·m⁻¹), vertical average loading rate (BW·s⁻¹), vertical instantaneous loading rate (BW·s⁻¹), and vertical net impulse (BW·s).

RESULTS

Tuck-Jump Assessment

Intrarater Reliability of Subjective Scoring

Within-sessions reliability was good to excellent for all items (ICC range, 0.67–1.00). The mean percentage exact agreement between sessions across all scoring criteria for all participants was 94.9% (range, 91.7%–100%). Intrarater reliability for the TJA total score was excellent (ICC = 0.99; 95% CI = 0.97, 1.00).

Changes in Subjective Scoring

Trivial to moderate changes that were not different were observed from prefatigue to postfatigue for the individual TJA criteria (Table 1), group TJA composite score (11 ± 3 to 11 ± 2; P = .93; Hedges g = 0.07), and number of jumps performed (16 ± 2 to 17 ± 2; P = .053; Hedges g = 0.20). Individual responses to fatigue indicated that, on average, 64% (range, 33%–92%) of participants had an unchanged score across the 10 criteria, and no participant demonstrated an increased lower extremity valgus severity score postfatigue (Table 1). Composite scores of ≥10 were evident in 58% (n = 7/12) of participants prefatigue and increased to 83% (n = 10/12) postfatigue.

Table 1. Median Tuck-Jump Assessment Scores for Individual Tuck-Jump Assessment Criteria²² Prefatigue and Postfatigue

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Changes in Kinetics

Our data showed small to moderate reductions from prefatigue to postfatigue in peak COM displacement (0.16 ± 0.02 m to 0.14 ± 0.03 m; P < .001; Hedges g = −0.69), time of jump cycle (0.66 ± 0.05 seconds to 0.62 ± 0.06 seconds; P < .001; Hedges g = 0.74), GCT (0.22 ± 0.03 seconds to 0.21 ± 0.03 seconds; P = .006; Hedges g = 0.41), FT (0.44 ± 0.03 seconds to 0.41 ± 0.04 seconds; P = .005; Hedges g = 0.68), jump height (0.24 ± 0.03 m to 0.21 ± 0.04 m; P = .003; Hedges g = 0.63), and vertical net impulse (0.44 ± 0.03 BW·s to 0.41 ± 0.05 BW·s; P = .003; Hedges g = 0.72). A small increase in tuck-jump kinetics was evident from prefatigue to postfatigue for k_leg (25.79 ± 7.43 BW·m⁻¹ to 29.41 ± 8.19 BW·m⁻¹; P = .005; Hedges g = 0.45) despite no changes in peak VGRF postfatigue (P = .73; Hedges g = 0.05; Figure 1). We observed no differences from prefatigue to postfatigue in the DF ratio (0.33% ± 0.03% to 0.34% ± 0.04%; P = .79; Hedges g = −0.09), vertical average loading rate (105.35 ± 18.71 BW·s⁻¹ to 109.98 ± 19.33 BW·s⁻¹; P = .12; Hedges g = −0.24), and vertical instantaneous loading rate (132.74 ± 17.24 BW·s⁻¹ to 135.95 ± 19.68 BW·s⁻¹; P = .41; Hedges g = −0.17).

Change in Jump Stabilization

The sequential averaging technique identified no mean differences in jump stabilization across all kinetic variables prefatigue to postfatigue (P > .05; Table 2). However, individual differences in jump stabilization were evident postfatigue, with 4 participants achieving stabilization 1 to 3 jumps earlier and the remaining 8 achieving stabilization 1 to 5 jumps later in the jumping cycle for all kinetic variables (Figure 2). Of the 8 participants, the stabilization ratio of all kinetic variables relative to the total number of jumps was earlier in the jumping cycle for 2 participants (prefatigue [56%] and postfatigue [52%] and prefatigue [55%] and postfatigue [52%]) despite stabilizing 1 jump later postfatigue (prefatigue [9] and postfatigue [10] and prefatigue [8] and postfatigue [9], respectively).

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Table 2. Stabilization of Tuck-Jump Kinetic Variables Prefatigue to Postfatigue

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DISCUSSION

The purpose of our study was to explore the effects of fatigue on ACL injury–risk variables by analyzing a repeated tuck-jump task using the visual 2D assessment, VGRF, and kinetic stabilization before and after an SSFP. Our findings indicated that, although scores for the visual 2D assessment did not change after the SSFP, female athletes adopted an altered jumping and landing strategy, reflected by an increased k_leg and decreased GCT, FT, jump height, peak COM displacement, and vertical net impulse, despite no changes in peak VGRF. In addition, kinetic stabilization was unaltered, but changes in kinetic stabilization varied between athletes.

Overall, athletes demonstrated no differences in TJA performance using the modified 2D assessment scoring after the SSFP, and consequently, our first hypothesis was rejected. This finding was contradictory to a previous report that identified an increase in composite scores and the number of flaws demonstrated post-Wingate fatigue protocol.¹² However, Vomacka et al used the original binary scoring (0 or 1) to identify the presence of technical flaws, which does not reflect the updated modified scoring and does not accommodate for the degree of severity for each criterion.¹² Furthermore, in our study, 58% of participants had a prefatigue composite score of ≥10, indicating that those athletes may have displayed undesirable lower limb biomechanics before completing the SSFP. This increased postfatigue, with 83% (n = 10) of participants demonstrating greater composite scores than baseline measures. The TJA composite score, therefore, should be interpreted with caution, and changes to the severity of technical flaws for each criterion should be used to detect fatigue-related changes. We suggest that the number of technical flaws demonstrated during the assessment provide more granular insight into an athlete’s individual response to fatigue than that of the criteria and composite scores.

Notwithstanding the lack of change in the TJA composite score after the SSFP, several changes were observed in the kinetic data. Peak VGRF is the most reported kinetic variable in fatigue-related research, and researchers have consistently shown that this variable is unchanged in healthy participants after exposure to fatigue protocols.³ Fatigue-induced alterations to peak VGRF were evident within our study; however, analysis of additional kinetic variables also revealed kinetic alterations that may place athletes at a heightened risk of injury. We identified reductions in GCT and vertical net impulse despite no changes in peak VGRF and DF ratio, which resulted in athletes jumping more quickly albeit at the expense of jump height. Data also showed increases in k_leg after the fatigue protocol, which, given the lack of change in peak VGRF, was explained by reductions in peak COM displacement during ground contact. Cumulatively, these results indicate that athletes altered their landing strategy by adopting a stiffer landing, possibly through reduced knee and hip flexion, which has previously been highlighted as a common mechanism of ACL injury due to excessive loading on the knee joint.⁸ Active mechanisms of vertical stiffness include the muscle activation and multijoint coordination of an individual to meet the physical demands of a functional task and are required for effective storage and use of the stretch-shortening cycle.^17,29 Researchers have suggested that excessive stiffness may increase the risk of injury due to increased shock, peak VGRF, and reduced joint motion in the lower extremity, which all may indicate a ligament-dominant landing strategy.¹⁰ Padua et al identified changes in muscle-activation patterns during repeated hopping protocols after fatigue, indicating that female athletes placed greater reliance on ankle and knee musculature and demonstrated a more quadriceps-dominant landing strategy.¹⁷ Such landing strategies can increase k_leg and increase the load on the ACL due to increased anterior tibial shear forces. Compared with a repeated hopping test, repeated tuck jumps for 10 seconds require greater multijoint coordination and neuromuscular control to sustain functional performance and comply with the technical constraints of the test. In our study, results of the visual 2D assessment suggest that athletes were at no greater risk of injury when fatigued (ie, no change in criterion severity); however, the presence of some degree of knee valgus when landing coupled with increased k_leg, due to reductions in peak COM displacement, would likely expose athletes to higher internal joint loads and thus greater risk of injury postfatigue. Practitioners should consider that changes in kinetics may increase athletes’ risk of injury in the absence of visual 2D assessment changes, and high levels of stiffness may place excessive load on the ACL.

We hypothesized that the variability of kinetics would increase when athletes were fatigued, with kinetic stabilization for all variables occurring later in the jumping cycle. At the group level, no differences were observed, so we reject our second hypothesis. However, unlike some of the uniform changes in kinetics after fatigue, the individual changes in stabilization were less consistent. Notably, some participants demonstrated a 20% to 30% stabilization change relative to their total jumping cycle postfatigue but demonstrated variations in TJA composite scores. For example, some participants who stabilized later (18%–22%) in the jumping cycle displayed no change in TJA score, some participants demonstrated smaller changes in stabilization (3%–4%) but a reduced TJA score, and 2 participants demonstrated a large change in stabilization (26%–30% earlier) but with a higher TJA score. In the absence of group-level changes, we suggest that the sequential averaging technique is not sensitive enough to detect changes in movement variability especially given the small sample size. Individual variations in stabilization warrant further research to understand the effect of fatigue-related kinetic variation and an individual’s relationship with injury risk that may help develop more personalized screening tools.

Notwithstanding the novel findings, our study had certain limitations. First, the sample size was small, which could reduce the generalizability of the findings. However, at least for some of the larger effects reported during the study (eg, changes in relative stiffness), post hoc analysis indicated that the study achieved a statistical power of 0.92 to 0.95. For some of the moderate changes in kinetics (eg, vertical net impulse), the study achieved a statistical power of 0.62. Therefore, caution should be applied to some of the results with smaller effects, which may require further study involving larger samples to provide more validation. Second, force-time data were extracted from a single force plate, so the relative contributions of individual limbs and potential associated asymmetries during the bilateral jumping task remain unclear. However, we are the first to examine the kinetic responses to fatigue during repeated tuck jumps, and our study provides novel data to better understand the effect of fatigue on ACL injury risk. Last, tuck jumps are a bilateral task and do not replicate the common single-legged mechanism associated with ACL injury. However, despite this limitation, the task is more functional than other jumping tasks more commonly adopted in research (eg, drop vertical jump) and reflects landing forces from self-regulated heights often demonstrated by athletes during training and match play.³⁰ Kinetic analysis of the repeated tuck jumps may, therefore, provide greater insight into individual jumping capabilities and the ability of the neuromuscular system to provide adequate stabilization and force attenuation,³⁰ especially in the presence of fatigue.

CONCLUSIONS

Kinetic analysis of repeated tuck jumps identified specific adaptations in jumping strategy in response to fatigue. Our findings indicated that visual 2D assessment used in isolation may not be sensitive for detecting fatigue-related alterations in jump-landing biomechanics that could increase the ACL injury risk. However, fatigue-induced disruption to landing kinetics may be most sensitive, particularly fatigue-induced increases in k_leg. This kinetic response to fatigue may alter joint kinematics, expose athletes to greater internal joint loads, and contribute to greater strain and shear forces on the ACL. Importantly, individual responses to fatigue are likely to influence kinetic stabilization across a range of variables. Notably, earlier kinetic stabilization during the task postfatigue may be due to alterations in jumping strategy and may not be reflective of athletes with greater resistance to fatigue; however, this warrants further research. Practitioners should be mindful that athletes may also present with undesirable and high-risk landing mechanics before fatigue, and thus, in the absence of alterations postfatigue, athletes would still be considered at risk of injury. Athletes with high-risk mechanics during the TJA should be targeted with corrective training strategies regardless of their susceptibility for exacerbation from sport-related fatigue. Finally, more rapid jumping rates resulting in greater stiffness on landing should be closely monitored when analyzing repeated tuck jumps after a fatiguing task, and when possible, kinetic analysis should be quantified to assess potential changes in kinetic strategies.