Analysis of the accuracy and reliability of vertical jump evaluation using a low-cost acquisition system

Recent literature highlights the vertical jump as an important assessment tool for variables such as lower limb power [1, 2], analysis of peripheral fatigue [3, 4], and domains of biomechanics to improve an athlete’s performance [3, 5]. Among the indices presented in an evaluation of the vertical jump, the value of flight time stands out [6, 7]commonly employed in clinical and scientific practice, as a reliable variable during the task. The vertical jump assessment can also be used to monitor the external load imposed in a workout, thus underlining the importance of applying its method. After volunteers took consecutive jumps, a calculation using the height reached and the impulse time was made so evaluators could be able to manage the training load of the participant based on these indices [8].

A recent systematic review [9] has provided data on the importance of other variables besides flight height that can be analyzed for performance evaluation. Indices such as power, peak velocity, peak force, and average impulse were highlighted. In this regard, considering the number of variables that the vertical jump can generate, many studies seek to find ways to evaluate it reliably. Thus, the use of a force platform for data acquisition stands out, currently being the gold standard of this evaluation. However, it imposes limitations given its cost and difficulty in transporting it from one site to another for data collection. A three-dimensional infrared camera system [10] and contact platforms [11] have been used as alternative methods. However, such resources still show access limitations due to their cost, transportation constraints, and apart from their dependence on electricity.

The high cost of the platforms and the limitations imposed on their daily application end up interfering with their use in different environments. The difficulty that professionals face in conducting vertical jump tests as evaluative means in environments outside standardized laboratories should be noted. As a matter of fact, cheaper methods have been used to evaluate jump performance, such as the Sargent test [12] and some research groups have assessed vertical jump using other tools, such as a specific phone app [13], associated with practical sports models and machine-learning scenarios [14], or even associated with different remarkable accessories to the gesture, such as the inclusion of specific shoes [15]. Studies such as [16] sought more cost-effective alternatives and used high-speed capture cameras to measure maximum vertical height and flight time with open-access software (Kinovea), observing high reliability and reproducibility when comparing data from an infrared platform and the captured images. However, although high-speed cameras are less expensive when compared to force platforms, professionals with fewer resources still need help to afford to use them. In this way, low-cost analysis models are a remarkable combination. As mentioned, tools such as the Kinovea software have been widely explored in sport practice scenarios, and the wide dissemination of smartphones around the world has configured an environment of noticeable insertion and considerable low cost when compared to other assessment instruments. Thus, this study aimed to evaluate the accuracy and the intra- and inter-rater reliability of maximum vertical height, impulse time, and flight time using open-access software (Kinovea) with video captured by a smartphone.

A total of 46 participants were recruited, with a mean age of 24.65 ± 3.80 years, a weight of 85 ± 16.90 kg, a height of 1.76 ± 0.07 m, and a body mass index of 27.25 ± 4.61 kg/m². The values for the vertical jump evaluation can be found in Table 1.

The intra-rater reproducibility for bipodal jumping showed ICC values ranging from 0.903 to 0.934 between impulse time, flight time, and maximum height, thus demonstrating excellent reproducibility. For the unipodal dominant and unipodal non-dominant conditions, it was observed that ICC values ranged from 0.713 to 0.950 and 0.874 to 0.902, respectively. Thus, moderate to excellent reproducibility was observed for these conditions. The complete values with SEM and MDC indices can be seen in Table 2.

The inter-rater analysis for the bipodal jump showed substantial to excellent reproducibility, with values between 0.823 and 0.926. For the dominant unipodal jump, moderate reproducibility (0.684 to 0.702) and the non-dominant unipodal jump, with moderate indices (0.554 to 0.690). The values can be seen in full in Table 3.

Higher ICC was thus found in the intra-rater reliability compared to the inter-rater analyses, and lower error percentages (SEM %) were found in the intra-rater reliability.

The validity of the metrics can be considered when compared to the correlation values between force platform and video jump analysis, where in the bipodal condition, a high correlation was observed for impulse time and flight time. Compared to unipodal gestures, a low correlation is shown between the methods, with only flight time and impulse time for the dominant limb showing moderate correlation, as well as for height with the non-dominant limb. All indices can be seen in Table 4.

In Figs. 1, 2, and 3 are exposed the graphs by Bland–Altman analysis regarding the bipodal and unipodal evaluations. The graphs corroborate the figures presented previously showing high correlation between the platform and the evaluators in bipodal jumps and a low in unipodal jumps.

In light of the need for assertive evaluations and reliable methods, we can observe a great data discrepancy among evaluators after analyzing the present study. However, when the intra-rater data is analyzed, it is possible to notice a greater reproducibility, especially during flight time. It is possible, consequently, to say that the videos analyzed in the Kinovea software can result in reproducible evaluations in the scope of flight time, which is the most used variable for evaluative methods [6, 7]. In this regard, the importance of the current study is based on the possibility of facilitating the process of vertical jump evaluation for various purposes already presented in the literature.

As initially highlighted, the search for evaluation methods for indices, such as the vertical jump height, considering the flight time and how some intervention can improve this performance, is shown to be not only necessary but also likely to be disseminated from the financial perspective. The outcome presented in this study showed that the videos could be performed using an ordinary smartphone and should always be analyzed by the same evaluator, with a certain degree of training, to present more reliable results.

These results are in line with the literature that points out that there is a vast preference for the use of smartphones and tablets in sports practice [24], either for the quality of applications or ease of use when compared to more robust software. However, not all the tools have been submitted to scientific methods for confirmation and validation of their service, as pointed out by another study of this group [25].

Due to the importance of the vertical jump evaluation, studies seek to find more accessible means for its analysis. The study by Balsalobre-Fernandez et al. [16] evaluated the movement of the jump using a high-speed camera and demonstrated reliable results when analyzed by two evaluators. Accordingly, the data presented here corroborate Balsalobre-Fernandez’s group and add important data to the literature since a common smartphone was used and showed reliable results.

Carlos-Vivas et al. [26] analyzed the time-of-flight correlation between a cell phone app and the force platform. The results showed high reliability, demonstrating that a low-cost device can present similar results to a more robust piece of equipment. These results confirm what was observed in the current study, where the images captured by the cell phone and analyzed in the Kinovea software showed a high correlation between flight time and impulse time for bipodal jumps. It should be noted, however, that only the flight time variable had been correlated, unlike our study, which included impulse time and maximum vertical height.

The vertical jump height was evaluated in the study by Pueo, Penichet-Tomas, and Jimenez-Olmedo [27], which compared the flight height measured by a high-cost system (Motion Capture System, composed of 8 infrared cameras) using a low-cost system (Smartphone-Kinovea). The results showed high reliability between both systems. In this regard, it reiterates the capability of low-cost front-end systems as a high-quality tool. It shows, therefore, the undeniable need for the information offered by the inclusion of new technologies into the evaluation environment, where the role of science is to filter and make such tools even better, as demonstrated by Loturco et al. [28].

Points of emphasis, such as reproducibility, can be discussed regarding the tool and the proposed gesture. Rodríguez-Rosell et al. [29] conducted an essay on the reproducibility between traditional and sport-specific gestures, demonstrating that among them, the countermovement jump, such as the one used here, can be considered a reliable and reproducible gesture of the evaluated demands, thus ratifying the proposed method. Still, regarding reproducibility, a point to be highlighted is the low rates among evaluators, especially for flight time. An important point is the take-off phase of the jump, as pointed out by Mackala et al. [30]. Different positions or the noticeable change between bipodal and unipodal may be enough to promote significant changes. It is important to underline that, once it is a study of validity between the acquisition methods, the participant’s gesture did not suffer feedback or specific biomechanical demands, which could be a factor of difference in the outcome.

A recent study [31] compared the use of video at different frame rates for jump height analysis. The study aimed to analyze whether ultra-high video speed would increase the accuracy of the analysis. The researchers concluded that videos with 240 Hz were sufficient as they did not show any relevant differences compared to videos with higher frame rates. Although the current recommendation for analyzing video jumps is for videos with higher frame rates, our study presents relevant results because even with a small frame rate, we still found data that allows the use of our method for, for example, bipodal jumps. Consequently, the present study can add to the current state of the art that videos recorded by smartphones, when analyzed with the Kinovea software, can be useful for the evaluation of the vertical jump in particular instances, with excellent reproducibility when measured by the same evaluator, and consistent values for clinical practice. Based on the fact that low-cost analysis models are a remarkable combination, the scenario of simple and ordinary acquisition and open-access software creates an environment of remarkable insertion and considerable low cost.

This study shows some limitations, such as the difficulty in standardizing key moments for biomechanical and gesture analysis. However, the proposal of the present study is based on the validity of the evaluative means. Moreover, the study only included healthy male individuals. Future studies should evaluate individuals of both genders with some dysfunction that may alter the analyzed gesture, and larger time windows may allow a more assertive analysis, for example.

The current study demonstrates that time-of-flight analyses of bipodal jumps can be performed using a smartphone-Kinovea system. Nevertheless, it should be noted that the use of this system is more reliable when analyzed by a single evaluator. For analysis of unipodal jumps, the present study did not observe data supporting the use of a smartphone for movement analysis.