The Concurrent Validity and Reliability of a Low-Cost, High-Speed Camera-Based Method for Measuring the Flight Time of Vertical Jumps : The Journal of Strength & Conditioning Research

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The Concurrent Validity and Reliability of a Low-Cost, High-Speed Camera-Based Method for Measuring the Flight Time of Vertical Jumps

Balsalobre-Fernández, Carlos1,2; Tejero-González, Carlos M.1; del Campo-Vecino, Juan1; Bavaresco, Nicolás2

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Journal of Strength and Conditioning Research 28(2):p 528-533, February 2014. | DOI: 10.1519/JSC.0b013e318299a52e
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The evaluation of vertical jumping is of great relevance in sporting performance as an indicator of fatigue conditions (8,9,17,18,20) and also it is well known that the height reached during a vertical jump is of great importance when determining the explosive strength of the lower limbs in numerous sporting disciplines (21,25,32). Furthermore, flight time is the most accurate and frequently used variable (6,10,16,28) in both studies on vertical jumping (4,6,16,22,27) and in the biomechanical analysis of athletic performance (4,8,15,19,22,27,30,31). In the case of vertical jumps, measurement of the flight time is currently the most valid and reliable means of calculating the height reached (3,10). The most commonly used methods for measuring flight time are (a) contact platforms (5,10,11,13,26), (b) infrared (IR) platforms (4,6,16), (c) video-based methods (10,13,28), and (d) force platforms (10–12,16,28), with the latter being considered the “gold standard.” Thus, numerous studies have used such instruments to calculate vertical jump heights, which are much more widely used in the field of sports training, based on flight times (8,17,18,20,23,24,31). As such, the use of methods for calculating the vertical jump height from flight times is a need in the field of sports training.

However, all these methods suffer from 3 potential drawbacks: first, they are rather expensive, which makes them difficult to acquire beyond some well-funded university laboratories and elite sports clubs; second, they are difficult to transport, especially in the case of heavy platforms, which, in turn, limits their applicability; and, finally, they need electric power outlets nearby to function, which also limits their use to certain contexts. For their part, some video-based methods are known to allow accurate, valid, and reliable flight time measurements when compared with the gold standard method because of their use of sophisticated high-speed cameras and video analysis software (10,13,28). Furthermore, as they tend to be powered by batteries, they can easily be used in all field situations. However, generally speaking, this equipment is relatively expensive and requires certain experience and training to ensure a correct use. All this points to the need for alternative, low-cost, and easy-to-use methods for measuring vertical jump flight times.

The purpose of the present study was to analyze the concurrent validity and reliability of a new measurement method (i.e., the HSC-Kinovea method) for the calculation of the flight time and height of vertical jumps using a low-cost, low-resolution, battery-powered high-speed Casio Exilim FH-25 camera (HSC), and open-license and easy-to-use video analysis software (i.e., Kinovea 0.8.15 for Windows; available at (7,29). We hypothesized that (a) this method should correlate well with the well-known and already validated method using an OptoJump IR platform (16), and (b) 2 non-trained independent observers will obtain similar flight time and jump height values when using the HSC-Kinovea method. If the validity and reliability of the HSC-Kinovea method were demonstrated, it could prove very useful for coaches and researchers in many sports.


Experimental Approach to the Problem

The study had an instrumental design and was conducted in a sports biomechanics laboratory. Each of the 25 subjects selected performed 5 vertical jumps (Counter Movement Jump [CMJ]) (18) on an OptoJump IR platform while simultaneously being recorded with a high-speed camera at 240 fps. More specifically, the CMJ was performed with both legs simultaneously, hands on the hips, from a static standing position, and was exerted at maximal effort; the landing was also on both feet at once. The number of jumps was set at 5 to find significant correlations in terms of α < 0.99, β < 0.10, and an intensity of covariation ≥0.35. A total of 125 jumps were analyzed.


The sample consisted of 25 physically active sports science students (7 women and 18 men) aged between 20 and 29 years (mean = 23.3 ± 3.7 years). The study was undertaken according to the Helsinki declaration, and all procedures were approved by the Ethics Committee of the Autonomous University of Madrid. No subjects trained in vertical jumping were required here because this study simply compares the same flight time of each jump using 2 different methods. Participation of the subjects was voluntary and anonymous, and all of them signed an informed consent form.


Both the IR OptoJump system single-meter kit (Microgate Co., Bolzano, Italy) (16) and a low-resolution 448 × 336-pixel (vs. 1,920 × 1,080 pixel of the full HD standard) HSC Casio Exilim FH-25 camera (Casio Computer Co., Ltd., Tokyo, Japan) were used to collect data for vertical jumps. The HSC camera recordings were subsequently analyzed using the open-license Kinovea software. The IR platform consisted of 2 optical sensors (measuring 100 × 4 × 3 cm in length, width, and height, respectively) connected to a laptop equipped with Windows 7 and the OptoJump v.3.01 software, which offers real-time values for each jump in milliseconds. The sampling frequency of the IR platform was 1 kHz (i.e., 1,000 records per second or 1 datum every millisecond). The HSC-Kinovea camera recorded at 240 fps, with a shutter speed of 1/4,000, and, as noted above, the data obtained were analyzed using open-license video analysis software (Kinovea 0.8.15 for Windows) (7). As was the case for the IR platform, each jump recorded using the HSC-Kinovea camera was measured in milliseconds. The jump height was calculated using the formula described in the literature (h = t2 × 1.22625) (16).


Vertical Jumps Performance

The participants completed a standard 10-minute warm-up composed of jogging, lower-body dynamic stretches, and vertical jumps. Then, they were instructed on how to perform the CMJ: hands on the hips, from static standing position, maximal effort and take off, and landing with both legs simultaneously. Each participant performed 5 practice jumps and then they performed 5 CMJ on the IR platform while being recorded with the high-speed camera. If 1 jump did not met the criteria for a successful jump (hands on the hips, static standing position, take off, and landing with both legs simultaneously), it was repeated.

Recording Conditions

To simulate a field-training situation and to determine the versatility of the HSC-Kinovea method, recording was performed under nonprofessional conditions. Thus, no tripod or lighting systems were used, and 1 researcher recorded all the jumps; to capture a close-up of each subject's feet, this researcher was lying prone on the ground, holding the camera at 1.5 m from the platform and oriented perpendicularly to the sagittal plane of the subject being assessed.

Measuring the Flight Time Using the HSC-Kinovea Method

To measure the flight time, 2 observers untrained in video analysis independently selected the first frame in which both feet had left the floor completely and the first frame in which at least 1 foot was touching the floor again and then used the software's “Timer” tool to obtain the final value. If the subjects lifted off or touched down again with 1 foot in a different frame to the other, the observers were told to record the first frame in which no foot was touching the floor (lift off) or the first frame in which 1 foot was touching the floor (touch down).

Statistical Analyses

All jumps were combined to give a total of 125 data points. After checking the normal distribution assumption by applying the Kolmogorov-Smirnov test, the reliability was calculated using the intraclass correlation coefficient (ICC) in 2 ways: (a) the ICC between the 2 observers in terms of the flight time and jump height estimated using the Kinovea video analysis software, and (b) the ICCs between the flight time and jump height obtained by each observer using the HSC-Kinovea method and that obtained using the IR platform. To determine the suitability of analyzing the correlation between the values obtained using the different instruments, these ICC values were later complemented with Bland-Altman graphical statistics (2). Similarly, the concurrent validity was calculated using the bivariate Pearson product-moment correlation coefficient (r). The limit of statistical significance was set at p < 0.05. All calculations were performed using IBM SPSS statistics 20 (IBM Co., Armonk, NY, USA) and MedCalc.12.2.1 (MedCalc Software, Ostend, Belgium).


The results obtained using ICC, in both 2-way random and absolute agreement, show a perfect reliability between observer 1 and observer 2 when estimating the flight time and jump height by Kinovea video analysis (ICC = 1, 95% confidence interval [CI] = 1–1, p < 0.0001). The absolute average difference between the 2 observers was 0.1 milliseconds in flight time and 0.0 cm in jump height (Figure 1).

Figure 1:
Bland-Altman plot between observer 1 and observer 2 (ICC = 1, 95% CI = 1–1, p < 0.0001). N = 125. The central line represents the absolute average difference in (A) flight time (−0.1 milliseconds) and (B) jump height (0.00 cm). The upper and lower lines represent 95% limits of agreement (differences of means ± 1.96 SD of the differences, respectively). ICC = intraclass correlation coefficient.

The bivariate Pearson product-moment coefficient showed an almost perfect correlation between the flight time values obtained using the HSC-Kinovea method and those obtained using the IR platform (both observers had the same values: r = 0.997, p < 0.0001). Moreover, the HSC-Kinovea method explained 99.5% (r2 = 0.995, p < 0.0001) of the differences (shared variance) obtained by the IR platform (Figure 2).

Figure 2:
Concurrent validity between IR and observer 1 (A) and between IR and observer 2 (B). Correlation between flight time values estimated using the IR platform and the HSC-Kinovea method; N = 125; r 2 = 0.995 (p < 0.0001). IR = infrared.

Furthermore, ICC, both in 2-way mixed and absolute agreement, showed an almost perfect agreement in terms of the flight time obtained by the 2 observers using the Kinovea software and the values obtained using the IR platform (the agreement for observer 1 and observer 2 was ICC = 0.997, 95% CI = 0.995–0.998, p < 0.0001). In this case, the absolute average difference between observer 1 and the IR platform was 2.2 milliseconds in flight time and 0.31 cm in jump height (Figure 3), whereas the absolute average difference between observer 2 and the IR platform was 2.1 milliseconds in flight time and 0.3 cm in jump height (Figure 4).

Figure 3:
Bland-Altman plot between observer 1 and the IR platform (ICC = 0.997, 95% CI = 0.995–0.998, p < 0.0001); N = 125. The central line represents the absolute average difference in (A) flight time (2.2 milliseconds) and (B) jump height (0.31 centimeters). The upper and lower lines represent 95% limits of agreement (differences of means ± 1.96 SD of the differences, respectively). IR = infrared; ICC = intraclass correlation coefficient; CI = confidence interval.
Figure 4:
Bland-Altman plot between observer 2 and the IR platform (ICC = 0.997, 95% CI = 0.995–0.998, p < 0.0001); N = 125. The central line represents the absolute average difference in (A) flight time (2.1 milliseconds) and (B) jump height (0.3 cm). The upper and lower lines represent 95% limits of agreement (differences of means ± 1.96 SD of the differences, respectively). IR = infrared; ICC = intraclass correlation coefficient; CI = confidence interval.


In light of these results, it can be concluded that the HSC-Kinovea method is extremely precise, reliable, and valid for measuring the flight time of vertical jumps. Indeed, the theoretical precision of this method (taking into account its sampling frequency) is very high (±millimeters, i.e., ±5.6 mm for a 563-millisecond jump), whereas the IR system has a theoretical precision of ±1.8 mm for the same flight time (with ±millimeters), always assuming that the jump is performed without altering the landing area (16). In light of these formulae, jump height calculations based on the corresponding flight times have 1 major drawback, namely that the measurement error increases with jump height. However, even if we were to evaluate the jump of a professional basketball player, who can reach jump heights of 60 cm (flight time of 700 milliseconds), the precision of the measurement (±7.02 mm) would still be high. As such, despite this inherent limitation to jump height calculations, the flight time remains one of the most widely used variables for this purpose (8,10,11,28).

Our study found an average difference between the 2 methods of 3.1 mm. This value is remarkable considering the 2 important characteristics of the Optojump IR platform: first, that it has a very high sampling frequency (1 kHz, recording 1 datum every millisecond), and, second, that it has been validated over a force platform (ICC = 0.998) and also achieves a very high test-retest reliability (ICC = 0.982–0.989). In light of this, it is hardly surprising that this system is considered to be the gold standard for measuring the flight time of vertical jumps (10–12,16,28). However, as can be seen from Figures 1, 3, and 4, there are a few outliers in which the difference between the 2 observers, and between the IR and HSC-Kinovea methods, is outside the confidence intervals. These outliers can be explained by a poor image quality because of the fact that neither professional lighting systems nor tripods were used. This means that a possible loss of focus or a shadow generated by the subject could have decreased the image quality. As such, and despite having demonstrated that the HSC-Kinovea system is highly accurate, we recommend to use the best possible recording conditions, although it should be stressed that professional filming is not required to obtain valid and reliable measurements.

Notwithstanding the quality of the IR platform, this study shows that the HSC-Kinovea method is equally as valid and reliable for measuring the time flight of vertical jumps as its more sophisticated and heavier counterpart. Although the values obtained with the HSC-Kinovea method are slightly lower than those obtained with the IR platform because of its lower sampling frequency (240 Hz of the HSC-Kinovea method vs. 1 kHz of the IR platform), the differences, in absolute terms, are quite small (−3.1 mm on average). This is quite remarkable considering that it consists of simply a light, simple high-speed camera of amateur recording quality and easy-to-use free video analysis software. Moreover, the present study demonstrates that recording at 240 fps and with low image resolution (448 × 336px) can also yield equally reliable and valid measurements as those obtained using professional cameras recording at speeds of 500–1,000 fps (14,15,28). The HSC-Kinovea method becomes even more appealing, in terms of its applicability, when taking into account that it requires no tripods, lighting systems, extra foci, or electric outlets. It should also be mentioned at this point that, unlike other methods, many of which require trained observers (1), the HSC-Kinovea method does not require previous experience in video recording and analysis. Proof of this was the perfect agreement between the measurements of the 2 untrained observers used herein (ICC = 1, p < 0.0001). Perhaps, its only drawback is that it does not provide the instant data outputs available when using other technologies (e.g., force, contact, or IR platforms). However, this does not seem to be overly problematic because the time required to obtain the data is quite reasonable for a study of this kind—both untrained observers took <30 seconds to determine the flight time of each jump and about 62 minutes to analyze all 125 jumps.

As far as the characteristics of the sample used in this study are concerned, it could be argued that the fact that the participants were not professional athletes could be a drawback of this study. However, as the aim of this research was to compare the same flight time using 2 different methods, in our opinion, the manner in which the jumps were performed is irrelevant. For the same reason, we think that analyzing 5 jumps from each participant, instead of 1 jump, from 125 independent participants is not a limitation. Therefore, in our opinion we could obtain similar results with 125 participants, but it could be less operational. Indeed, to guarantee a sufficient simple size of 125 jumps, we decided to use 25 sports science students, who were asked to perform 5 jumps each.

At least 2 new research lines emerge from the above. The first one would be to consider whether or not even cheaper slow motion technologies (e.g., smartphones) could also yield valid and reliable measurements of vertical jump flight times. If that were the case, these type of measurements could easily be performed almost anywhere. The second one would imply studying whether or not the HSC-Kinovea method exhibits the same validity and reliability when measuring other variables traditionally obtained with the IR platform, such as the contact time of the stride of sprinters (4,14,19,22,27). Positive results in this regard would be useful for many sports coaches and researchers.

Practical Applications

As indicated above, coaches and trainers can benefit from use of the HSC-Kinovea method to measure the flight time and height of their athletes' vertical jumps. This method is much cheaper than an IR platform and is highly operational because the high-speed camera is fully portable and can be used directly in field situations. In addition, the Kinovea software is very easy to use and does not require previous experience in video analysis to obtain highly accurate and reliable measurements. Thus, coaches and trainers can now obtain highly accurate, valid, and reliable flight time data for the vertical jumps of their athletes simply by videotaping them and analyzing the videos on a personal computer. This could help them to better control their training programs as performance in the vertical jump is known to be an excellent indicator of explosive strength in the lower limbs and the degree of neuromuscular fatigue. This video-based method, however, has a small drawback because it does not provide immediate results. Nevertheless, even an untrained observer can obtain the flight time of a jump in about 30 seconds. Finally, to estimate the height of the jump from the flight time, coaches and researchers can use the formula indicated in Dias et al. (10), which establishes that the height of the vertical jump maintains a second degree polynomial relationship with the flight time: h = t2 × 1.22625, where h is the jump height in meters and t is the flight time in seconds.


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video analyses; slow motion; biomechanics; free software

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