Introduction - Assessing Jump Performance Using Force Plate Analysis
"Force plate analysis" is a biomechanical analysis performed in sports to provide valuable information about an athlete's movement patterns, performance, and injury risk and involves the use of a specialized platform equipped with "pressure sensors" to measure the "ground reaction forces" (GRFs) generated during physical activities. This analysis can provide insights into different factors such as kinematics, kinetics, power and stability of an athlete (Badby et al., 2022). Some of the common applications of force plate analysis in sports include "Jump analysis", "Sprint analysis", "Balance and stability assessment", and Change of direction analysis. The current report aims to analyse jump square and countermovement through force-plate analysis, along with the fatigue mechanisms that are related to the athlete's movement. The report has been prepared to illustrate the importance of measuring jump performance in sports.
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It has been found that "Jump performance" is an important aspect of many sports, as it can be a key indicator of an athlete's explosive power, strength, and overall physical fitness. In terms of athlete performance, many sports, such as basketball, volleyball, and track and field, require athletes to jump as a fundamental skill. In this type of sport, an athlete's ability to jump high or far can directly impact their performance. According to Dietze-Hermosa et al., (2020), vertical jump performance has been a significant predictor of sprint as well as agility performance in basketball players, especially in young females. Further, jump performance has also been used as an indicator of an athlete's injury risk. As mentioned by Arundale et al., (2020), athletes with poor jump performance were more likely to experience injuries than those with good jump performance.
Similarly, according to Jones et al., (2020), improving an athlete's jump performance through training can help reduce their risk of injury. Jump performance can be used as a measure of an athlete's physical fitness, as it requires a combination of power, strength, and coordination. According to Whitehead et al., (2019), jump performance has been significantly correlated with overall physical fitness in male collegiate athletes. Lastly, it can be used as a tool for talent identification in certain sports, as it can help identify athletes with potential for success. As opined by Moeskops et al., (2020), jump performance was a significant predictor of future success in elite female gymnasts.
Figure 2: Pressure mapping in force plate
According to Marcote-Pequeño et al., (2019), a study conducted on female soccer players to analyse the force, velocity, and power output of countermovement jumps found that peak force and peak power were significantly correlated with jump height, while peak velocity was not. Further, the study found that higher levels of fatigue were associated with decreases in peak force and power, but not peak velocity. Moreover, another study conducted by Wells et al., (2022), found that the "squat jump" (SJ) had higher peak force as well as peak power than the "countermovement jump" (CMJ), but lower peak velocity. The study also concluded that squat jumps had a higher rate of force development than countermovement, suggesting that it may be a better indicator of explosive power. A study found that fatigue led to decreases in peak force, power, and velocity in both jumps, with a greater decrease in peak power in SJ compared to CMJ (Marshall et al., 2021).
CMJ and SJ are two common movements used to assess lower body explosive power and performance. Kinetic analysis of these movements, specifically the forces and moments acting on the lower body joints, can provide insights into the underlying biomechanics and muscle activation patterns involved in the jump. Additionally, understanding how fatigue affects these kinetics can inform training programs aimed at improving jump performance and reducing injury risk. The hip and knee joints contribute the most to the total jump performance, with the hip joint producing the highest power output, however, fatigue led to decreases in peak power output, with the hip and knee joint moments being most affected. Further, fatigue led to increased activation of the knee extensors during both jumps, with the greatest increase occurring in SJ (Donahue et al., 2021).
Method
For force plate analysis, first consent from the participants has been collected, explaining the nature of the study, its purpose, and what will be expected of the participant. This ensures that the participant is fully aware of what they are participating in and the potential risks involved. Then, the participant's ages, heights, and masses were recorded to ensure that the data collected could be standardized and compared across participants. After that, a dynamic warm-up was performed to prepare the participant for the jumping tasks and to reduce the risk of injury, including heel flicks, jogging, high knees, self-selected "dynamic stretches", and "3 countermovement jumps" (CMJs) (Baritz, 2020). The participants were given an opportunity to practice the jumping task to become familiar with the equipment and task requirement. After that, the first set of observations was taken, including "3 CMJs" and "3 squat jumps" (SJ) with a "2-second pause" at the "bottom of the jump".
The participant used the standard technique with "hands on hips" throughout the jump, and the starting jump was randomized. The aim was to land the jump where the take-off was from, and there was a 15-second rest period between each trial. Next, a 4-minute control period was introduced where the participant is instructed to stand still and not move to measure their baseline static standing force (Badby et al., 2022). Then a second set of observations was made following the protocol of the first observation. Then a fatigue intervention was during including, including a "cycle ergometer" or "sprint interval training" (SIT), where participants were asked to perform "4 x 15-second sprints" with a "3 to 1 work rest ratio", using a load of "7%" of their body mass. Finally, a third set of observations was made. The collected data was used to calculate "jump height", "peak force" and "net impulse".
Limitation
Force plate measurements can be affected by participant factors such as body mass, centre of mass, and movement variability. These factors can influence the accuracy and reliability of the data and make it challenging to compare results across different participants (Baritz, 2020). Further, it provides information on the forces acting on the ground, but it does not provide information on the internal forces and muscle activations that produce the external forces, thereby limiting the understanding of the underlying biomechanics of a movement.
Results
The graphical representation of the results observed for different participants has been done, and the findings for the standard deviation and the mean value have been estimated further.
Figure 3: Graphical representation of the data according to various participants.
Findings
The findings were observed for the standard deviation and the mean value for the result of the different participants.
Figure 4: Standard deviation and the Mean of the output
The demographic of the participants was also observed
Figure 5: Data for the Demography
The graph for the demography was also recorded
Figure 6: Graphical representation of the demography
The representation of the different aspects of the demographic was observed in the graph. The blue color indicated the code for the participant, the orange color was representing the Height, the grey represented the Mass, and the yellow code represented their age difference. The further findings and their discussion has been discussed in the discussion part below.
Discussion
From the overall results, it has been observed that the jump height and the peak forces were given differently for each individual. The net impulses were also measured for CMJ and SJ. Finally, the overall mean and the standard deviation were observed according to which the graph was obtained further as the finding (Campa et al. 2019). For participant number 2100417, in the case of CMJ, there were 3 participants, for number 1 the jump height was measured to be 0.22, the peak force was 1268, and the net impulses were 167.15 respectively. As compared to SJ in the case of the number 1 participant, the jump height was recorded as 0.24, the peak force was observed to be 1327 and the net impulses were found to be 159.25 respectively (Ristea et al. 2020). In the case of the number 02, the jump height was 0.20, the peak force was 1252 and the et impulses were recorded to be 161.87 respectively. Comparing number 02 with the SJ, the jump height was found to be 0.23, the peak force was 1367, and the Net impulses were recorded to be 158.63 respectively. Number 03 has given the record in the case of CMJ to be 0.16 as the jump height, the peak force was recorded to be 1197 and the Net impulses were found to be 142.02. In comparison to SJ, the 03 showed the jump height to be 0.19, the peak force was found to be 1212, and the Net impulses were recorded as 149.95. For this case, the graph was found to give real force more than the 1200 range, and the Net impulse to be less than 200 in the case of CMJ and for the SJ the peak force has given the horizontal lines till the margin of 1400 with the same result for net impulse as shown in case of CMJ.
For the participant 2100842 in the case of CMJ for 01, the jump height was observed to be 0.34, the peak force was 1464 and the Net impulse was 259.16 respectively. For 02 the jump height was 0.34, the peak force was recorded as 1448, and the Net impulses were found to be 257.07 respectively. and Finally, for the 03 number, the Jump height was observed to be 0.29, the peak force was 1463 and the Net impulse was found to be 247.59 respectively (Rathleff et al. 2020). In comparison to SJ, the jump height for 01 was recorded to be 0.29, the peak force was calculated to be 1519, and the peak force was observed to be 1519 giving the net impulse 210.68 respectively. For 02 and 03, the jump height was 0.30 and 0.30 respectively, peak force was recorded to be 1498 and 1440 respectively and the net impulse was 210.06 and 199.86 respectively. The observed graph was recorded.
Overall 15-16 participants had taken part in the experiment, and the output results were observed accordingly. Almost all the participants' results showed a positive graphical representation, and they represented their output as a horizontal bar. The mean and the standard deviation were recorded for CMJ and SJ. The graph was recorded further and the horizontal peak line was observed further. The mean was taken for 01, 02, and 03 in the case of CMJ and 01,02,03 in the case of SJ, In the case of the CMJ the reading was observed to be 0.26for the jump height, and the peak force was observed to be 1451 and the Net Impulse was observed to be 225.90. For the 02 case, the jump height was recorded to be 0.26, peak forces were recorded as 1447, and the Net Impulses were recorded to be 189.28. For the SJ, the jump height was recorded to be 0.25, the peak force was recorded to be 1452, the Net Impulse was recorded to be 201.51. For the 02 and 03 cases, the jump height was observed to be 0.26, the jump height, 1447 as the peak height, and the Net Impulse was observed to be 227.56 and 189.28 for the 03 number respectively (Bruinvels et al. 2021). For the demographic analysis, the participant's height, age, and mass were taken into consideration, which were observed to be different in different cases (Macey et al. 2021). The standard deviation was observed to be 7.7 in the case of the height, the overall mass was observed to be 10.9, and the age was observed to be 3. The mean value was recorded as 173.6 for the mean for all participants, 70.6 for the mean of mass, and age 21.0 for the mean values.
Conclusion
This report discusses the different results that have been found in the sports for different participants. The lab report represents those data with different methods and theories, further, it uses the graphical representation for the result or the output based on the different participants. The mean and the standard deviation were recorded and the graphs were provided in the form of Horizontal bars. All the findings and the discussion have been further in detail, which helps in understanding the overall tasks and gives a better analysis of the experimental sports done with different participants.
References
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