The weightlifting derivatives are considered a primary resistance training modality within strength and conditioning programs (38). Previous research has indicated that training with these exercises has resulted in superior adaptations in strength-power qualities when compared to alternate methods such as jump training (42), traditional resistance training (4), and kettlebell training (32). Although a previous study by Helland et al. (18) may contradict the idea that training with weightlifting derivatives is a superior method, it should be noted that a number of limitations, some acknowledged by the authors, may have served as confounding variables. For example, the weightlifting training group in the previous study only included weightlifting exercises (e.g., clean, hang clean, snatch, etc.), a greater overall training volume combined with increased training intensities (near failure or to failure), limited information about the training status of the subjects (potential lack of training transfer), and both men and women were included in the sample. Taken collectively, a greater body of the literature supports the notion that weightlifting derivatives produce superior overall training effects when properly programmed. The effective transfer of training stemming from the weightlifting derivatives is a consequence of their ability to load the triple extension of hips, knees, and ankles, and span multiple portions of the force-velocity curve (38), while also influencing intermuscular coordination and skill (1,2,31).
There are several variants of the weightlifting derivatives that can be used, each with differing kinetic and kinematic characteristics (38). However, the majority of research into these lifts has focused exclusively on lifts executed from the hang (generally between the knee and midthigh) such as the hang power clean (36,41), jump shrug (35,41), and hang high pull (37,41). Although there are several advantages to exercises performed from the hang position, including the stimulation of the stretch-shortening cycle, a limitation is the absence of the first pull. In lifts that contain both a first and second pull, larger amounts of force are produced (13,26,34), enabling the triple extension to be executed against greater loads (10). The limited research into these lifts may be due, in part, to the complications associated with the numerical integration of force-time data at the initiation of the first pull.
Best practice methods for the collection, processing, and analysis of force-time data from strength qualities assessments have become increasingly commonplace in the sports science literature, with attention placed on identifying the initiation of the action of interest (11,30,33). For example, the isometric midthigh pull (IMTP) requires an accurate determination of the initiation of the pull to reliably calculate rate-dependent variables. A number of methods have been reported including fixed values such as 20 or 40 N above baseline, or a change of >5 SDs during the initial weighing period, with the latter suggested as the preferred approach (11). When analyzing a countermovement jump (CMJ) force-time trace, the point at which to commence the analysis will impact the integration process resulting in changes to the derived velocity and power measures. The threshold values for this test have included the instant at which force is reduced by 4 × the SD of body mass (BM) (23) or an arbitrary reduction in force (e.g., >10 N) (12). Recently, 30 ms before a 5 × SD of BM decrease in the force-time curve has been suggested as the criterion method because it retains the entire jump signal while minimizing any capture of the stance phase (33).
A common requirement across these force-time curve analyses is a stable period of consistently applied force preceding the action in a trial (referred to as the weighing phase) (5,11,29). Although this is generally easy to achieve, the realities of performance testing in high-pressure–applied settings are such that “clean” data are not always gathered. The ability to capture a weighing phase before movement onset is reduced further when weightlifting derivatives containing a first pull are being analyzed due to the starting position required. If data are acquired by a force platform, the lifter + barbell system must not be in contact with any other surface (e.g., plates on the floor) (7,8,22). This ensures that system mass is unchanged allowing velocity to be calculated through numerical integration of the force-time curve. It is recommended then that lifts incorporating the first pull must therefore be performed approximately from the mid-shank instead of the floor (23). However, considering the position of the lifter and the loads involved, it can be challenging for the performer to maintain a stable period of force application before the initiation of the pull. Consequently, conventional approaches to movement identification such as those used in the CMJ and IMTP may not be feasible. Understanding the impact of different methods for identifying movement onset during a weightlifting derivative with both a first and second pull will enable practitioners and sports scientists to better explore the mechanical characteristics of these lifts. Despite the benefits associated with reliable analysis of such exercises, there are no known studies into this topic and limited research in general into exercises such as the snatch pull and clean pull (13,38). Therefore, it is the purpose of this investigation to examine the impact of different movement onset thresholds (5% above system weight [SW], the first sample above SW, or 10 N above SW) on the reliability of common performance variables during a weightlifting derivative containing both a first and second pull when lifting from the mid-shank. In addition, the influence of weightlifting ability (as assessed by the 1 repetition maximum [1RM] power clean) on these reliability measures will also be explored. It was hypothesized that a larger onset threshold (in this case, the 5% above SW) would improve the reliability of measures extracted from the force-time record of such a lift, and that greater reliability will be displayed by the stronger subjects.
Experimental Approach to the Problem
The impact of different first-pull onset thresholds on the reliability of a series of force, velocity, and power measures during a weightlifting pulling derivative was examined using a cross-sectional within- and between-subjects design. All subjects attended a single testing session that was initiated with a standardized general then specific dynamic warm-up. Subjects performed 2 nonconsecutive maximal effort snatch-grip pulls (SGPs) from the mid-shank at 70% of their predetermined power clean 1RM. In addition, subjects were stratified based on their relative 1RM power clean result to determine the influence of weightlifting ability on the reliability of the dependent variables.
Fourteen recreationally trained men (mean ± SD: age: 25.21 ± 4.14 years [age range: 18–34 years old]; BM: 81.1 ± 11.4 kg; height: 1.79 ± 0.09 m; and 1RM power clean: 1.0 ± 0.2 kg·BM−1) who had been undertaking at least 6 weeks of instructed resistance training with the weightlifting derivatives, including SGPs, participated in this study. All subjects provided written informed consent, and the study was approved by the Bellberry Human Research Ethics Committee (2016-04-269).
Testing occurred >72 hours after any training sessions. Before testing, subjects completed a warm-up consisting of several unweighted activities including squats at increasing depth, alternating lunges, and submaximal CMJs and hops at increasing intensities. Subjects then completed the SGP at progressively increasing loads. This exercise is typically completed from the floor; however, during the present investigation, it was executed from the mid-shank level. This resulted in the entire mass of the barbell-lifter system being projected through the feet of the lifter. After completion of all warm-up activities, subjects had 3 minutes of passive recovery before undertaking at least 2 maximal effort trials at 70% of their predetermined 1RM power clean. Each trial was separated by 2 minutes of passive recovery. Subjects were instructed to keep the bar as still as possible before performing the trial with maximal intent. The bar was positioned at the mid-shank as determined via observation by the chief investigator. This qualitative approach enabled an increased ecological validity, which was necessary for this investigation. Subjects were cued to keep the arms straight until the triple extension was completed, and shrug at the top of the movement. In addition, the lifter was permitted to jump if the effort resulted in it. All trials were performed with the barbell-lifter system isolated on a force platform (Bertec Corporation, Columbus, OH, USA) with the data sampled at 2000 Hz using a data acquisition device (NI USB-6259 BNC, National Instruments, Austin, TX, United States) and processed using a custom LabVIEW program (V.12.0f3; National Instruments). Data were then saved off-line for secondary processing.
A custom-designed spreadsheet (Excel, version 2016; Microsoft Corp., Redmond, WA, USA) was used to calculate the dependent variables from the raw force-time data. The initiation of the lift was identified as the point at which the force-time curve increased by: (a) 5% above SW; (b) the first sample above SW; or (c) 10 N above SW. The end of the lift occurred at the lowest point on the curve >20 N. The force-time data were then numerically integrated between lift initiation and lift completion to generate a velocity-time record. This was achieved by dividing net force (vertical force − SW) by system mass and then integrating the product using the trapezoid rule on a sample-by-sample basis. The product of the force and velocity at each sample produced a power-time curve. Two distinct peaks occur during the SGP, which were used as events to denote force-time phases of the lift. The end of the first peak phase was identified as the first peak in force, whereas the end of the unweighting phase (i.e., start of the second peak) occurred at the first increase in force preceding the second peak (Figure 1). These phases were defined as they represented objective events that could be clearly identified in the force-time record in the absence of motion capture data previously used in earlier investigations (13,14). First peak mean rate of force development (RFD) was calculated as the change in force with respect to time between the initiation and end of the first peak phase. This metric was also calculated between the start of the second peak phase and the highest force value in that phase. Peak force, velocity, and power were indicated by the highest respective sample in the first and second peak phases. Average force, velocity, and power were calculated over the entire duration of the first peak phase. During the second peak phase, these variables were calculated between the start of this phase and the point at which the force-time curve dropped below SW. This instant represents the onset of the propulsion deceleration phase whereby the velocity of the system begins to reduce until the momentary pause (i.e., zero velocity) attained at the end of the second peak phase (Figure 1).
Data were normally distributed, except for the following variables: peak velocity and peak power in the first peak phase, and average force and RFD during the second peak phase. Where normality was met, a repeated-measures analysis of variance (group × onset condition) was executed with a post hoc Bonferroni correction to locate the presence of a difference in a given dependent variable between the 3 onset methods during the first trial. A Friedman test was administered for non-normally distributed variables followed by a Wilcoxon signed-ranks test with a Bonferroni correction. An alpha level of p ≤ 0.05 represented statistical significance. Cohen's d effect size calculations were performed to compare the magnitude of difference in dependent variables between trials, with thresholds set at <0.2, 0.21–0.5, 0.51–0.8, and >0.8 for trivial, small, moderate, and large magnitudes of effect, respectively. When assessing between-trial reliability for each onset method, data were analyzed using Microsoft Excel (version 2016; Microsoft Corp.) and are presented as group mean values ± SD. Reliability was assessed using a coefficient of variation (CV) and intraclass correlation coefficient (ICC) with associated 90% confidence intervals (90% CIs) (21). High reliability was deemed as a CV of <5% and an ICC of >0.90. An acceptable threshold of reliability was set at a CV of <10% and an ICC of >0.80 (24). Paired comparisons with a significance of p ≤ 0.05 were used to compare dependent variables between the 2 trials within each onset condition. To determine the impact of weightlifting ability on reliability, the cohort was stratified into 2 groups based on their 1RM power clean result (stronger: 1RM power clean >1 × BM, n = 6; age: 24.67 ± 4.37 years; BM: 79.72 ± 2.25 kg; and height: 1.74 ± 0.05 m; weaker: 1RM power clean ≤1 × BM, n = 8; age: 26.5 ± 3.12 years; BM: 82.15 ± 14.85 kg; and height: 1.82 ± 0.08 m). Reliability was assessed at both the whole cohort and stratified the group level. The CV and ICC, in addition to their associated CI, were calculated using a custom-designed spreadsheet (24). The SPSS (version 22; IBM, New York) was used to analyze all remaining data.
The mean and SD for all dependent variables in both trials at the 5%, first sample, and 10 N onset thresholds are presented in Tables 1–3, respectively. Figures 2–4 depict the CV and ICC for the dependent variables across all 3 onset thresholds for the entire group and when stratified by the strength level. First peak phase peak force and all second peak phase kinetic variables were unaffected by the method of movement onset, whereas the impact on the remaining second peak phase variables was negligible. At the whole group level, first peak phase peak force and average force achieved excellent reliability regardless of the onset method used. Similarly, during the second peak phase, peak force, average force, and peak velocity achieved either excellent or acceptable reliability in all 3 onset conditions. In the 5% method, the stronger subjects achieved acceptable reliability across all dependent variables, except for first peak RFD, second peak RFD, and average power. The reliability was generally reduced to unacceptable levels at the first sample and 10 N method across all first-pull measures except peak force. A similar pattern was seen within the weaker subjects, although with mostly lower levels of reliability overall when compared with the stronger group (Figures 5–7).
The aim of this study was to assess the influence of different onset thresholds on the reliability of kinetic and kinematic variables during a weightlifting derivative containing both a first and second pull. The primary finding was that the method used to identify the initiation of the lift (and therefore commence the analysis) had a considerable impact on the reliability of measures of system velocity, power, and RFD during the first peak phase. Specifically, of the 3 approaches examined, the 5% above SW threshold resulted in generally improved reliability across all such measures, particularly for the stronger group. It should be noted, however, that at the whole group level, the only variables to achieve reliability were second peak phase peak velocity, and peak and average force across both peak phases. These findings illustrate the difficulty of conducting force platform assessments of weightlifting variations that include the first pull (where the barbell must be held slightly off the ground), if other variables such as power and velocity of the system are of interest. Nevertheless, this study has illustrated how selecting an appropriate onset threshold can lead to improved reliability of these data.
The major limitation with the first sample method was that the subjects often applied force slightly greater than that of SW when attempting to maintain a stable bar before the lift was properly initiated. This is, indeed, a problem that is induced by not being able to commence the lift from the floor due to the requirement to account for entire SW as part of force-time data analysis procedures. Furthermore, it can be expected that the difficulty in stabilizing the bar would be increased under additional load and will consequently limit the relative load that can be used. As RFD and all remaining average variables are calculated directly from this instant, incorrect identification of initiation of the lift has a major impact on the accuracy of the values attained. An additional disadvantage of this method is the impact it has on velocity. The onset point indicates the start of motion of the system and therefore influences the velocities (peak and average) attained, particularly in the first peak phase. For example, in the first sample method, it is more likely (due to the low force threshold) that numerical integration of the force-time record commences before the actual initiation of the lift, consequently affecting the calculation of velocity, which will subsequently affect the calculation of power. Any inaccuracies associated with velocity and power calculations in the first peak phase, despite this phase not eliciting “high” velocity and power values, will continue into the second peak phase, thus rendering these and similar calculations made throughout the entire SGP meaningless. It should be noted that although “maximal” acceleration and velocity is not the focus of the first pull (as noted in considerably lower power outputs in this and other investigations (15,20)), if technique is maintained, this may result in greater velocity and displacement and, therefore, increase the kinetic and kinematic outputs during the lift, or result in an increased load lifted.
Many of the issues present in the first sample method are largely overcome in the 10 N and 5% thresholds. The advantages to these approaches are that the analysis commences after any erratic movement of the system preceding the major force application at the beginning of the lift. As 5% of SW in this present investigation represented 67 ± 10.20 N, further unstable ground reaction force (GRF) before the initiation of the exercise was avoided, and reliability generally improved further when compared with the 10 N threshold. However, the improvements in reliability between the 10 N and 5% methods were not as marked as those noted between the first sample and 10 N approaches. Performing the SGP with an SW greater than what was used in this study would likely increase the chances of a 10 N threshold being prematurely exceeded before the lift is initiated (i.e., doubling SW would effectively half the 10 N threshold when expressed as a percentage of the SW). Thus, the 5% method is likely the most sensible option from those included in this study, but further research is required to determine if this approach remains the most appropriate across a range of loads in the SGP.
None of the onset thresholds included in this study accounted for the noise in the force signal that would be generated by the force platform itself (i.e., residual force) throughout the entire data collection period and by the subjects themselves during the weighing period (i.e., before initiating the movement). This is usually achieved by establishing SW (or BM, if performing a BM-only task) over at least a 1-second duration before the onset of movement and then calculating an onset force threshold based on 5 times the SD of the established SW. Using a 5 SD of the SW approach, similar to the 5 SD of the BM approach advocated for IMTP (11) and CMJ (33) force-time testing, was not possible in this study, however, because of subjects having to commence the lift while holding the barbell off the floor at the mid-shank level. If, however, researchers use force platforms that are large enough to accommodate both the subject and barbell in the start position of any weightlifting derivatives that commence from the floor, they should consider comparing the 5 SD of the SW approach with the 5% method used in this study. The 5 SD of the SW onset threshold approach should also be considered when performing force platform assessments of weightlifting variations from the knee (i.e., hang position) or above (i.e., midthigh level), given that it is much easier to maintain a stable position (and thus, establish SW from the force-time record) before executing such lifts. Further research could explore the benefits and limitations of alternate methods for processing force-time data of lifts with a first and second pull. This may include collecting a standing weighing period to obtain SW before and after the lift, yet within the same force-time record. However, such methods will be susceptible to integration drift because of the large capture period.
The results from the current study indicate that stronger individuals appear to demonstrate greater reliability when it comes to producing force-, velocity-, and power-time data during the SGPs performed, regardless of the threshold method used. Although not examined in the current study, stronger individuals may have been able to replicate their technique compared with weaker individuals. Because muscular strength benefits an individual's performance in a number of ways, including maintaining posture (39), it is possible that stronger individuals can produce greater performance outcomes despite potential flaws within their technique compared with weaker individuals (19). Although limited longitudinal research on the performance of weightlifting variations following changes in technique exists (17,43), Winchester et al. (43) demonstrated considerable improvements in power snatch bar-path kinematics following only 4 weeks of training with the weightlifting derivatives. Furthermore, superior reliability in weightlifting performance has been previously reported among stronger vs. weaker Olympic level weightlifters (28).
The current study is the first study to compare different starting thresholds during a weightlifting variation and should, therefore, serve as hypothesis-generating research. As mentioned above, a common issue that arises when examining weightlifting variations that typically start from the floor (e.g., power clean, clean/snatch pull from the floor, etc.) is the fact that the entire system mass is not taken into account on the force platform before the start of the lift. As a result, much of the research examining weightlifting variations has been performed from a hang position (e.g., midthigh, the knee, or below the knee) (36,40). The current study and previous studies (6,7) have circumvented this issue by starting the lifts from a paused position at the mid-shank after the load has been lifted slightly off the ground. It should be noted that 2 studies (9,27) were able to examine the external power output produced solely from GRF data during the clean exercise. However, it is unclear what starting thresholds were used to identify the start of each lifting phase.
It is important to note that the phases of the SGP (first peak, unweighting, second peak) in this study were identified solely on the intact force-time curve. Although this approach enabled an objective identification of the phases using only GRF data, the segmental position of the lifter is needed to precisely define the pull phases. Previous research within weightlifting (3,14–16,25) has used joint and barbell kinematics to define specific phases of the snatch. For example, Harbili and Alptekin (16), among others (3,14,25), defined 5 phases of the snatch, with the pull and transition portions being described as; lift-off to first maximum knee extension (first pull), first maximum knee extension to first maximum knee flexion (transition) and first maximum knee flexion to second maximum knee extension (second pull). This indicates that knee joint kinematics are a key criterion in defining the phases of the pull.
A limitation of this study was that no 3D motion capture system was used to identify moments occurring in the knee joint; therefore, the authors were unable to identify the phases using methods previously mentioned. However, a standardized objective method using solely GRF data was used to identify key phases of the lift. Using objective points on the force-time curve allows future research to standardize methods when measuring weightlifting pulling movements. Furthermore, as the kinetic and kinematic behavior of the entire system is generally of greater relevance to the strength and conditioning coach, it seems practical to establish procedures for identifying phases from GRF data in the absence of motion capture. It would be of interest to practitioners for future research to explore, in detail, methods of weightlifting phase identification derived from GRF data alone and to establish how this compares to combined methods of joint and barbell kinematics along with GRF data.
Analyzing changes in the force-time curve of the weightlifting derivatives can yield valuable mechanistic information on lift performance. However, to do so requires suitable data processing techniques that produce reliable measures of performance. The results from the current study indicate a considerably improved reliability using the 10 N and 5% method, when compared with the first sample procedure. However, the 5% method is recommended as the preferred option, as it is proportional to the load being lifted. Finally, practitioners can expect that as performance in the weightlifting derivatives improves, so too does the reliability of the kinetic and kinematic variables acquired from such a lift.
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