Assessing a smartphone application to measure counter-movement jumps in recreational athletes

Abstract

The use of counter-movement jumps as a measure of neuromuscular performance in athletes has become common in the sport setting. Accurate methods of measuring jump parameters are often expensive, difficult to transport and require expert knowledge. A new smartphone application (My Jump) claims to be a valid and reliable tool for assessing jump height but is yet to be evaluated by independent researchers. Sixty-one recreational athletes (30 male/31 female, mean ± SD; age: 20 ± 4 years) each performed three counter-movement jumps (totalling 183 jumps) on a force plate following a standardised warm-up. All jumps were recorded using an iPhone 6 s and analysed for jump height (m) and flight time (s) using the My Jump application. Jumps were compared between a force plate and My Jump for validity with inter-scorer reliability also assessed. Results show that My Jump is valid (mean bias = 0.9 cm, r = 0.96) and reliable (typical error of estimate = 1.4 cm) for assessing jump performance in recreational athletes using an iPhone 6 s with a 240 Hz high-speed camera. My Jump is a cost-effective and easy-to-use alternative for measuring vertical jump performance without the need for specialist equipment or expertise.

Keywords

Force plate neuromuscular performance vertical jump

Introduction

A commonly used form of neuromuscular ballistic assessment in the sport setting is the vertical jump test. The vertical jump has many derivations that enable information to be gathered about various neuromuscular and performance qualities of an individual athlete.¹

Many different protocols and devices have been used to assess lower body power via the vertical jump test.² These include the use of yardsticks, contact mats, optical encoders, position transducers, accelerometers and force plates. Force plates are the most commonly validated measuring devices in the literature and are therefore regarded as the ‘gold standard’ for measuring jump performance.³ However, this method can be expensive, not particularly portable and often requires expertise for testing and analysis of the jump data.

The My Jump smartphone application uses the recording capability on an iPhone and requires researchers to select the take-off and landing frame on the video of a jump. From these two frame selections, the My Jump application calculates jump height and flight time. My Jump has been evaluated previously by the designers of the application,^4,5 reporting high intra-class correlation coefficients (ICC) (0.97–0.99), almost perfect Pearson correlations (r = 0.97–0.99), small mean differences (0.2 cm) and Bland–Altman bias (1.1 cm) between the application and a force plate. However, these results are yet to be confirmed by independent researchers using the latest smartphone technology.

Methods

Participants

Thirty male and 31 female (mean ± SD; age: 20 ± 4 years; body mass: 76.4 ± 15.2 kg) participants volunteered to take part in the current study. Participants represented a wide range of abilities and training status, from recreational to highly trained athletes. This was to ensure that the My Jump app could be validated across a wide range of jump heights. To be eligible for the study, all participants were required to be free from lower-limb injuries that may have affected their ability to perform vertical jumps. This study was given ethical approval by the Human Research Ethics Committee at the University of Waikato.

Methodology

The validity of a smartphone app (My Jump) to measure counter-movement jump (CMJ) performance was determined by comparing the jump height and flight-time measurements obtained simultaneously with two dual-axis force plates (Dual-Axis Force Platform, PASCO, California, USA) sampled at 200 Hz. Validity was assessed by comparing the My Jump app to the ‘gold standard’ force plate during a single testing session. Following a standardised warm-up including 10 external hip rotations, 10 internal hip rotations, 10 frontal plane leg swings, 10 sagittal plane leg swings, 5 single leg Romanian deadlifts, 10 body weight squats, 10 forward lunges and 3 submaximal jumps at 70, 80 and 90% of perceived maximum effort, each participant performed three maximal CMJs to a self-selected depth on the force plates. Participants kept their hands on their hips for all jumps, with their legs kept straight during the flight phase of the jump. Each jump was separated by 5 s. To assess inter-scorer reliability of the My Jump application, two members of the research team independently scored 50 jumps of the same video footage using My Jump.

Materials

The smartphone app used in the current study calculated the flight time of the CMJ by identifying the take-off and the landing frames of the video, and then transforming it into a jump height using the following equation described in the literature⁵

h = t^{2} \times 1.22625

(1)

where h is the jump height in metres and t is the flight time of the jump in seconds. The same equation was also used to calculate jump heights from the force plate data using customised software (WeightRoom, High Performance Sport New Zealand-Goldmine, Auckland, New Zealand). To record the CMJ with My Jump, a researcher lay prone to the ground with an iPhone 6 s (Apple Inc., USA) facing the participant (in the frontal plane), at a distance of 1.5 m from the force plate, focusing on the feet of the participant. Once a jump was recorded, the first frame in which both feet were off the ground (take-off phase) and subsequently, the first frame in which at least one foot was touching the ground (landing-phase) were selected in My Jump in order to calculate jump height and flight time. The iPhone 6 s used in the study included a 240 Hz high-speed camera, at a quality of 720 p.

Statistical analysis

All data are presented as means ± SD unless stated otherwise. Statistical significance was set at p < 0.05. Comparison of My Jump with the ‘gold standard’ force plate was achieved using a range of previously described methods including paired t-tests, Pearson product-moment correlation analysis, standard linear regression, 95% limits of agreement (LOA), mean bias (%) and typical error of estimate (TEE).^6–8 The magnitude of correlation between My Jump and the force plates was assessed using the following thresholds: <0.1, trivial; 0.1–0.3, small; 0.3–0.5, moderate; 0.5–0.7, large; 0.7–0.9, very large and 0.9–1.0, almost perfect. A Breusch–Pagan test was used to determine heteroskedasticity. Inter-scorer reliability data were analyzed using an Excel spreadsheet for reliability.⁸

Results

There was almost perfect agreement between the My Jump and force plate for both jump height (r = 0.96) and flight time (r = 0.96, Table 1). The mean bias between My Jump and the force plate for jump height was 0.9 ± 0.2 cm, which was associated with a TEE of 2.0 cm (Table 1, Figure 1). My Jump showed very good inter-scorer reliability (TEE = 1.4 cm, ICC = 0.97, Table 2). The results rejected heteroskedasticity at p < 0.05, indicating that there was no heteroskedasticity present across a wide range of jumping abilities.

Table 1.

Comparison of the force plates and My Jump app for jump height (cm) and flight time (ms), showing the mean bias, the range of mean difference, typical error of estimate (TEE – raw and %) and the Pearson’s moment correlation (r) between the two methods.

	Force plates (Mean ± SD)	My Jump (Mean ± SD)	Mean bias raw (Mean ± SD)	Range of mean difference (±2SD)	TEE* (raw) (90% CI)	TEE* (%) (90% CI)	Correlation (r)
Jump height (cm)	25.1 ± 7.5	25.9 ± 7.9	0.9 ± 0.2	−3.2–5.0	2.0 (1.8–2.2)	9.7 (8.9–10.7)	0.96 (0.96–0.97)
Flight time (ms)	448 ± 67	455 ± 69	8 ± 5	−30–45	19 (17–20)	4.6 (4.3–5.1)	0.96 (0.95–0.97)

2SD: two standard deviations; 90% CI: 90% confidence interval.

Figure 1.

The level of agreement plots (Bland–Altman) showing 95% limits of agreement (represented as dashed lines) between the force plate and My Jump for (a) jump height (cm) and (b) flight time (ms). Solid black line represents the mean bias between methods.

Table 2.

Inter-scorer reliability when using the My Jump device to calculate jump height.

Scorer 1 Jump height (cm)	Scorer 2 Jump height (cm)	TEE (cm) (90% CI)	CV% (90% CI)	ICC (90% CI)
27.5 ± 7.6	26.2 ± 7.5	1.4 (1.2–1.7)	5.8 (4.9–7.0)	0.97 (0.95–0.98)

Note: Means and standard deviations for both scorers are shown alongside absolute typical error of estimate (TEE), coefficient of variation (CV%) and intra-class correlation coefficients (ICC) for the comparison between scorers. Data shown as means ± SD unless stated otherwise. 90% CI = 90% confidence interval.

Discussion

The findings from the current study would suggest that My Jump is a valid measurement tool when compared to the ‘gold standard’ force plate. This was identified by a low mean bias (0.9 cm) and typical error of estimate (2.0 cm) and an almost perfect correlation (r = 0.96) when the two methods were compared (Table 1). This is the first independent study to assess My Jump and is in agreement with previous studies from the designers,^4,5 who described similar levels of ICC (0.97–0.99), Pearson correlations (r = 0.97–0.99) and mean differences (0.2–1.1 cm) using similar methods to the current study. My Jump also resulted in very small differences (TEE = 2.4 cm) in jump height between researchers scoring the same video footage, with no previous experience using the application (Table 2), indicating high levels of inter-scorer reliability. Future researchers and practitioners using the My Jump application should ensure that they are using a high-speed camera, such as the one used in the current study (240 Hz), as cameras with lower frame rate and resolution may significantly reduce the accuracy of scoring the jumps. The authors would also suggest that the jumps are performed in adequate lighting conditions and at a maximum distance of 1.5 m from the front of the jumper. We conclude that the My Jump application is a cost-effective and easy-to-use alternative for measuring vertical jump performance in athletes when using an iPhone 6 s.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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