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Received October 24 2024, accepted February 19, 2025, date of publication March 10 2025.

Original Research Article

Feasibility and Reliability of the My Jump 2 Smartphone 
Application in Measuring Peak Power, Flight Time and Jump 
Height in Physically Active Subjects during Two Different 
Jumping Tasks

Amândio Dias1,2,3,*, Paulo Pires4, Leandro Santana5, Paulo Marques6, Mário Espada3,4,7,8,9, Fernando Santos4,8,9, Eduardo 
Jorge Silva6, 10 and Diogo Teixeira6,10

1 Egas Moniz Center for Interdisciplinary Research (CiiEM); Egas Moniz School of Health & Science, Caparica, Almada, Portugal.
2 Integrative Movement and Networking Systems Laboratory (INMOV-NET LAB) - Egas Moniz Center for Interdisciplinary Research (CiiEM),           

Egas Moniz School of Health & Science, Caparica, Almada, Portugal.
3 Sport Physical Activity and Health Research & Innovation Center (SPRINT), Rio Maior, Portugal.
4 Centre for the Study of Human Performance (CIPER), Faculdade de Motricidade Humana, Universidade, de Lisboa, Cruz Quebrada-Dafundo, 

Lisboa, Portugal.
5 Postgraduate Program in Physical Education, Federal University of Juiz de Fora, Minas Gerais, Brazil.
6 Faculty of Physical Education and Sport, Lusófona University, Lisbon, Portugal.
7 Comprehensive Health Research Centre (CHRC), Universidade de Évora, Évora, Portugal.
8 Life Quality Research Centre (CIEQV), Complexo Andaluz, Apartado, Rio Maior, Portugal.
9 Instituto Politécnico de Setúbal, Escola Superior de Educação, Setúbal, Portugal.
10 Research Center in Sport, Physical Education, and Exercise and Health (CIDEFES), Lisbon, Portugal.

* Corresponding Author Email: adias@egasmoniz.edu.pt

ABSTRACT

Muscle strength and power are often evaluated through jumping tasks. This study investigates the reliability of My Jump 2 
(MJ2), a smartphone application (app) used for this assessment. Two commonly used jumps, the countermovement jump (CMJ) 
and squat jump (SJ), were analyzed. The study aimed to evaluate the reliability of MJ2 for assessing peak power, jump height, and 
flight time. Materials and Methods: Thirty-eight undergraduate students performed three jumps of each type in a randomized 
order. All jumps were executed on a contact mat and simultaneously recorded by the smartphone’s slow-motion camera. Two 
independent researchers analyzed the video data by identifying take-off and landing frames to calculate flight time. The intra-
class correlation coefficient (ICC), coefficient of variation (CV), and Lin’s concordance correlation coefficient (CCC) were used 
for comparison. Results: Excellent reliability (ICC > 0.9) and high agreement were observed for flight time and jump height in 
both SJ and CMJ. Typical error and CV analysis indicated low variability for SJ, whereas CMJ jump height showed greater vari-
ability. However, peak power reliability and agreement were low (ICC < 0.5) for both jumps. Conclusions: The results suggest 
that MJ2 is a reliable and valid tool for assessing jump height and flight time, irrespective of the device used for data analysis. 
However, its power measurement capability differs from a contact platform’s, likely due to the indirect methods used to estimate 
power. Based on these findings, the MJ2 app can be confidently used to measure flight time and jump height but should be used 
cautiously when assessing power.

Keywords—Jumping, Reliability, Testing, Power, Countermovement jump, Squat jump.            



Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

J Global Clinical Engineering Vol.7 Issue 1: 2025 40

Copyright © 2025. This is an open-access article distributed under 
the terms of the Creative Commons Attribution License (CC BY): Creative 
Commons - Attribution 4.0 International - CC BY 4.0. The use, distribution or 
reproduction in other forums is permitted, provided the original author(s) 
and the copyright owner(s) are credited and that the original publication 
in this journal is cited, in accordance with accepted academic practice. No 
use, distribution or reproduction is permitted which does not comply with 
these terms.

INTRODUCTION

In sports requiring continuous body movement, jumping 
is a fundamental task that relies on optimal lower-body 
coordination. These movements result from efficient energy 
transfer between lower limb joints,1 and are essential for 
athletic success.2 Vertical jumps are widely used to assess 
lower limb neuromuscular performance, as they correlate 
with injury risk prediction and athletic performance while 
serving as an indicator of power output.3,4

The squat jump (SJ) and countermovement jump 
(CMJ) are the most commonly analyzed jump types.3 
Jump height represents a key metric of neuromuscular 
performance. Mechanical power, a crucial component of 
sports performance, is often derived from jump height, as 
both SJ and CMJ require athletes to generate substantial 
mechanical work in a short duration.3 This appears to 
be a critical factor in sports performance, distinguishing 
athletes by level,5 experts vs. non-experts,6 and related 
to sports performance characteristics, such as jumping.7,8 
As body weight is used to normalize power, it could be 
highlighted that individual power can significantly affect 
jump performance and, subsequently, reach jump height.9 

Traditional instruments for assessing vertical jumps 
include force platforms, contact mats, linear position 
transducers, infrared cells, and optical systems.10–12 
However, these devices can be cumbersome, expensive, 
and require technical expertise, limiting accessibility for 
sports professionals.4,13 Recent technological advance-
ments have led to the increased use of mobile applica-
tions for real-time exercise assessment.14 This type of 
assessment allows for increased familiarity for athletes 
(assessment at their training site), easy portability, and 
removes many constraints of time, space, and equipment/
facilities required.15,16 The high level of technology now 
available, combined with the ease of transport and use, 

emphasizes using mobile devices to assess physical exer-
cise in real-time and store data for subsequent analysis.17 

Smartphone applications and wearables have been one 
of the most regular trends in the fitness industry in re-
cent years18 and present a cheaper alternative to other 
evaluation instruments. The My Jump 2 (MJ2) app was 
developed as a user-friendly, portable tool to accurately 
measure jumping performance.19

Several studies have validated MJ2 for jump height 
assessment in various populations, including active 
adults, children, elderly individuals, and athletes with 
cerebral palsy.4,13,20–24 High intra-rater reliability has 
been demonstrated across multiple jumping types.25,26 
However, limited research has assessed the app’s ability 
to measure power.

Yingling et al.27 used the jump height data from the 
MJ2 app to assess peak power using Sayer’s peak power 
equation.28 The results reported were mixed, as they in-
dicate excellent reliability for consistency between MJ2 
and the force platform, but poor to excellent reliability 
for absolute agreement. According to the authors, the dif-
ference in the results could be explained by the fact that 
MJ2 uses time in the air for its calculations and does not 
consider the upper limb reach component of the jump, as 
measured by the force platform. Another study compared 
the MJ2 app and a force platform for assessing reactive 
strength index and mean power during a drop jump.22  
The results showed near-perfect levels of agreement for 
the reactive strength index, but a weaker agreement for 
mean power. According to the authors, this may be related 
to the different means of assessing power between MJ2 
and the force platform. There is a lack of studies on the 
validity of power calculations derived from the MJ2 app. 
This means the data provided are still questionable and 
should be used cautiously.29 To the best of our knowledge, 
no further studies have been conducted to assess other MJ2 
app metrics, with most studies focusing on jump height.

 Given the discrepancies in previous findings, further 
investigation is necessary. This study aims to analyze 
the validity, feasibility, and reliability of MJ2 for power 
measurement while providing additional evidence on 
its accuracy in measuring jump height and flight time.



41 J Global Clinical Engineering Vol.7 Issue 1: 2025

Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

METHODS   

Participants

Sample size estimation was conducted based on the 
work of Donner et al.,30 targeting a reliability of 0.8 with 
a minimum of 0.6, 90% power, a significance level of 0.05, 
and a 10% dropout rate, resulting in a required sample 
size of 36 participants.

A total of 38 undergraduate sports science students 
(34 males, 4 females; mean age: 21.84 ± 3.48 years; body 
mass: 69.24 ± 11.29 kg; height: 1.74 ± 0.09 m) volunteered. 
Inclusion criteria required participants to be free of lower 
extremity injuries or pain within the past three months. 
Written informed consent was obtained, and the study 
was approved by the Ethics Committee of the Polytech-
nic Institute of Leiria (CE/IPLEIRIA/22/2021), which 
considered the procedures mentioned in the Helsinki 
Declaration.31

Instruments  

The study was conducted in a controlled laboratory 
setting. A Xiaomi Mi 11 Lite smartphone (version 14, 
Xiaomi, Beijing, China) recorded participants’ feet in the 
frontal plane at a 1.5-meter distance19 and a height of 30 
cm using a tripod.32 This position allowed for a clear view 
of the participant’s lower extremities to ascertain take-off 
and landing moments. The smartphone’s slow-motion 
camera recorded at 240 Hz with a 720-pixel resolution. 
Video data were exported for later analysis. Two inde-
pendent evaluators analyzed the data: one using an iPad 
Mini-5 (version 16, CA, USA) (OBS-Ipad) and another us-
ing a MacBook Air M1 (version 15, CA, USA(OBS-Mac). A 
ChronoJump contact platform (version 1.9, ChronoJump 
Boscosystem, Spain) was used as the reference device 
for comparison. The validity of this platform has been 
previously established.33   

Design and Procedures                      

This was an observational study, in which all data collec-
tion was conducted in a single session. The MJ2 app and 
contact platform simultaneously recorded all the jumps 
performed by the participants. Before data collection, 
the same evaluator took measurements of leg length and 
hip height at 90° knee flexion (distance from the greater 

trochanter to ground) since they are required for calcu-
lations in both the MJ2 app and Chronojump software. 

Each participant completed a standard warm-up of 
dynamic stretching followed by three trial practices in 
total.34 Participants performed three SJ and three CMJ 
trials, with a 30-second rest interval between each. The 
jump order was randomized, and verbal encouragement 
was provided. SJ required a squat position of ~90° of knee 
flexion, held for 2 seconds before jumping. Participants 
kept their hands on their hips for all jumps. Trials failing 
to meet the criteria were repeated. Subjects performed 
three SJ and three CMJ with a rest period of 30 s. between 
them. The order of jumps for each participant was ran-
domized. All participants received verbal. All participants 
were required to refrain from vigorous physical exercise 
24 hours before the testing and were properly dressed 
to perform the jumps. For safety purposes, there was a 
space of 1 m in front and sides of the contact platform. A 
whiteboard was placed in the back of the frame (Figure 
1), with a specific coding, so that in the posterior analysis 
performed, observers could identify the subject and jump. 

 

FIGURE 1. Data collection setup.

The same coding was used to record data on Chrono-
jump software. Two evaluators with experience utilizing 
the MJ2 app independently assessed each of the 228 jumps 
(6 jumps for each of the 38 subjects), with a total number 
of 456 observations. Both observers have a Ph.D in sports 
science and previous experience working with strength 
and conditioning programs. For video analysis, observers 
manually determined take-off and landing frames, using 
the criteria for selecting video frames: both feet were off 
the ground (take-off) and at least one foot touched the 
ground (landing), as suggested earlier.19 The videos were 



Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

J Global Clinical Engineering Vol.7 Issue 1: 2025 42

used for CV% was , where sd is 
the standard deviation and for TE was   .41 

High reliability was determined if ICC > 0.90 and CV < 
5%.42 The usefulness of the test was defined as “Marginal” 
(TE > SWC), “OK” (TE = SWC), and “Good” (TE < SWC).43

The agreement was calculated using Lin’s concordance 
correlation coefficient (CCC) using a custom-made Excel 
spreadsheet based on Lin’s recommendations.44–46 Values > 
0.95 were deemed necessary to consider a good agreement.43

RESULTS  

Table 1 presents the descriptive information regarding 
the participants, also used for MJ2 and the contact platform.

TABLE 1. Descriptive Statistics of Participants and Performed 
Measurements.

Variables Total Subjects Male Subjects
Female 

Subjects

Age (years) 21.84 ± 3.48 21.88 ± 3.51 21.50 ± 3.20

Weight (kg) 69.24 ± 11.29 71.47 ± 9.58 50.25 ± 5.31

Height (m) 1.73 ± 0.08 1.75 ± 0.07 1.58 ± 0.03

Leg length 
(cm) 102.68 ± 16.27 103.03 ± 17.06 99.75 ± 5.72

Height at 90° 
flexion (cm)

63.53 ± 6.50 63.59 ± 6.66 63.00 ± 4.85

Note: Values are expressed as mean ± SD.

Intra-observer and contact platform reliability results 
for CMJ and SJ flight time, height, and power, are presented 
in Tables 2 and 3. The ICC scores were > 0.90 in all cases, 
indicating good reliability. 

Inter-rater reliability scores are presented in Table 4 
for CMJ and Table 5 for SJ. In both the CMJ and SJ, flight 
time and height ICC scores were > 0.90, and CV was below 
5% in all situations except OBS-Ipad vs. platform (CV = 

not analyzed in any consistent order of participants or 
jumps. Data retrieved for comparison were flight time, 
jump height, and power. In the MJ2 app, peak power es-
timations were based on the work of Samozino et al.,35 

with the following equation +1)   , with m 
the body mass, g the gravitational acceleration,  hp0 the 
vertical push-off distance, and h the jump height. The 
contact platform estimated peak power with the Sayers 
equations.28  .

Statistical Procedures

Descriptive statistics were presented as mean ± standard 
deviation. Shapiro-Wilk tests assessed normality. Systematic 
bias between observations was tested using paired t-tests, 
and effect sizes were calculated.36 The highest scores of the 
three jumps in each technique were used for calculations. 
Standardized mean differences (95% confidence intervals; 
CI) and Hedges’s g corrected effect size37 were calculated 
to determine the magnitude of change and compare 
observations, where the effect size (ES) was considered 
trivial if g < 0.2, small (0.2–0.5), moderate (0.5–0.8), 
large (0.8–1.60), and very large (> 1.60).38 Reliability 
was assessed through Intraclass Correlation Coefficient 
(ICC) calculations. For intra-rater observations, a two-way 
random effect absolute agreement single rater ICC (3, 1) 
was used; for inter-rater, a two-way random effect absolute 
agreement multiple rater ICC (3, k) was performed.39 ICC 
values < 0.5 were considered indicative of poor reliability, 
values of 0.5–0.75 were indicative of moderate reliability, 
values of 0.75–0.90 were indicative of good reliability, 
and values > 0.90 suggested excellent reliability.39 All 
these tests were performed using Statistical Package for 
Social Sciences (SPSS, v26, IBM Corp., Armonk, NY, USA). 

Additionally, Typical Error (TE), expressed as the coefficient 
of variation (CV%), and the smallest worthwhile change 
(SWC; 0.2 of the between-subjects standard deviation) were 
calculated through the use of the Excel spreadsheet provided 
by Hopkins40 to support reliability analysis. The formula 



43 J Global Clinical Engineering Vol.7 Issue 1: 2025

Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

the flight time was rated as Good for OBS-Ipad vs. OBS-
Mac and OBS-Ipad vs platform and Marginal for OBS-Mac 
vs. platform. In the SJ results, all observations were rated 
as Marginal in the height analysis. 

All agreement results for CMJ and SJ indicate good agree-
ment between observers and the platform (CCC > 0.95). 
Exceptions were verified for CMJ and SJ power analysis, 
where in all cases the CCC was < 0.15, thus reflecting no 
agreement when contrasted with the platform.

8.8) and OBS-Mac vs. platform (CV = 8.7). Moreover, in 
CMJ and SJ, when testing for power, OBS-Ipad and OBS-
Mac vs. platform ICC scores were < 0.50, indicating poor 
reliability, thus precluding further analysis. 

Significant paired differences were observed in 
both observers and the platform results in the CMJ (p = 
0.001) and SJ (p = 0.04). ES (g) results were, however, 
all trivial (< 0.2). As for usefulness, the CMJ results 
for flight time were rated as Good, and for the CMJ 
height  they were rated as Marginal.  In the SJ results,  

Variables
OBS-Ipad OBS-Mac Contact Platform

Mean ± SD ICC (95% CI) Mean ± SD ICC (95% CI) Mean ± SD ICC (95% CI)

Flight Time 
(ms)

Jump 1 516.201 ± 54.067 515.528 ± 53.288 5,22.500 ± 52.639

Jump 2 514.646 ± 48.469 0.921(0.871; 0.955) 517.112 ± 48.886 0.917 (0.864; 
0.953) 5,22.921 ± 47.442 0. 912 (0.855; 

0.950)

Jump 3 519.742 ± 47.899 519.447 ± 49.201 5,26.053 ± 47.467

Height (cm)

Jump 1 33.024 ± 6.523 32.930 ± 6.431 33.781 ± 6.422

Jump 2 33.139 ± 5.997 0.920 (0.868; 0.954) 33.076 ± 6.038 0.917 (0.863; 
0.953) 33.777 ± 5.917 0.911 (0.855; 

0.950)

Jump 3 33.398 ± 5.952 33.377 ± 6.108 34.163 ± 6.010

Power 
(Watts)

Jump 1 1,592.916 ± 
381.748 1,574.776 ± 385.070 9,46.045 ± 330.540

Jump 2 1,594.180 ± 
385.424 0.963 (0.937; 0.979) 1,582.117 ± 388.016 0.961 (0.934; 

0.978) 9,49.240 ± 345.460 0.994 (0.990; 
0.997)

ICC (95% CI): Interclass correlation coefficient with upper and lower confidence intervals. 

TABLE 2. Intra-observer and Contact Platform Reliability for Countermovement Jump Performance Variables. 



Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

J Global Clinical Engineering Vol.7 Issue 1: 2025 44

Variables
OBS-Ipad OBS-Mac Contact Platform

Mean ± SD ICC (95% CI) Mean ± SD ICC (95% CI) Mean ± SD ICC (95% CI)

Flight Time 
(ms)

Jump 1 506.151 ± 52.384 505.081 ± 52.458 510.921 ± 50.382 

Jump 2 508.442 ± 53.189 0.929 (0.868; 0.963) 507.540 ± 53.238 0.930 (0.965; 
0.964) 514.684 ± 51.208 0.931 (0.866; 

0.965)

Jump 3 518.440 ± 56.659 518.158 ± 56.724 523.947 ± 54.610

Height (cm)

Jump 1 31.742 ± 6.426 31.611 ± 6.416 32.274 ± 6.244

Jump 2 32.036 ± 6.569 0.926 (0.860; 0.961) 31.926 ± 5.541 0.926 (0.855; 
0.962) 32.756 ± 6.398 0.928 (0.857; 

0.963)

Jump 3 33.342 ± 7.062 33.308 ± 7.083 33.996 ± 6.883

Power 
(Watts)

Jump 1 1488.335 ± 
338.602 1506.616 ± 368.425 926.492 ± 334.469

Jump 2 1504.804 ± 
359.699 0.943 (0.892; 0.970) 1520.048 ± 369.943 0.947 (0.900; 

0.973) 931.680 ± 331.032 0.994 (0.988; 
0.997)

Jump 3 1562.984 ± 
380.007 1579.455 ± 379.079 948.434 ± 338.721

 ICC (95% CI): Interclass correlation coefficient with upper and lower confidence intervals.

TABLE 3. Intra-observer and Contact Platform Reliability for Squat Jump Performance Variables.



45 J Global Clinical Engineering Vol.7 Issue 1: 2025

Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

TABLE 4. Interreliability for Countermovement Jump Performance Variables.

* P< 0.05; CMJ: countermovement jump; ES: effect size; CI: confidence interval; ICC: intraclass correlation coefficient; 
TE: typical error; CV: coefficient of variation; SWC: smallest worthwhile change; (95% CI): Upper and lower confidence 
intervals.

CMJ Flight Time (ms) CMJ Height (cm) CMJ Power (W) 

 OBS-Ipad 
vs OBS-Mac

OBS-Ipad 
vs Platform

OBS-
Mac vs 

Platform

OBS-
Ipad vs  

OBS-Mac

OBS-Ipad 
vs Platform

OBS-
Mac vs 

Platform

OBS-Ipad 
vs 

OBS-Mac

OBS-Ipad 
vs Platform

OBS-Mac 
vs Platform

Paired diff. 
(cm) (95% 

CI)

0.30 (-1.51; 
2.10)

−6.31 
(−8.53; 
−4.01)*

−6.61 
(−8.45; 
−4.76)*

0.02 (−0.20; 
2.47)

−0.77 
(−1.05; 
−0.48)*

−0.79 
(−1.02; 
−0.56)*

−0.75 
(−15.16; 
13.67)

638.82 
(512.27; 
765.36)*

632.33 
(505.64; 
759.02)*

Paired ES 
(g) 0.01 0.13 0.14 0.01 0.13 0.13 0.01 1.84 2.7

ICC (95% 
CI)

0.99 (0.99; 
0.99)

0.99 (0.93; 
0.99)

0.99 (0.89; 
0.99)

0.99 (0.99; 
0.99)

0.99 (0.94; 
0.99)

0.99 (0.91; 
0.99)

0.99 (0.99; 
0.99)

0.25 (−1.89; 
0.594)

0.26 (−1.88; 
0.601)

CCC (95% 
CI)

0.99 (0.08; 
0.999)

0.98 (0.97; 
0.99)

0.98 (0.97; 
0.99)

0.99 (0.99; 
0.999)

0.98 (0.98; 
0.99)

0.99 (0.97; 
0.99)

0.99 (0.99; 
0.99)

0.14 (0.019; 
0.261)

0.15 (0.022; 
0.266)

TE (95% 
CI)

0.08 (0.06; 
0.10)

0.10 (0.08; 
0.13)

0.08 (0.07; 
0.11)

0.18 (0.15; 
0.23)

0.45 (0.37; 
0.58)

0.44 (0.36; 
0.57)

CV (95% 
CI)

0.80 (0.6; 
1.0) 1 (0.8; 1.2) 0.80 (0.7; 

1.0) 4 (3.3; 5.2) 8.80 (7.2; 
11.6)

8.70 (7.1; 
11.4)

SWC (cm) 1.1 1.35 1.12 0.14 0.17 0.14

Rating Good Good Good Marginal Marginal Marginal



Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

J Global Clinical Engineering Vol.7 Issue 1: 2025 46

TABLE 5. Interreliability for Squat Jump Performance Variables.

SJ Flight Time (ms) SJ Height (cm) SJ Power (W) 

OBS-Ipad vs 
OBS-Mac

OBS-Ipad 
vs Platform

OBS-Mac vs 
Platform

OBS-
Ipad vs 

OBS-Mac

OBS-Ipad 
vs Platform

OBS-
Mac vs 

Platform

OBS-Ipad 
vs 

OBS-Mac

OBS-
Ipad vs 

Platform

OBS-
Mac vs 

Platform

OBS-Mac OBS-Ipad vs 
Platform

OBS-Mac vs 
Platform

2.94 
(−22.62; 
28.50) 

636.70 
(505.57; 
767.82)*

634.85 
(510.51; 
759.20)*

Paired diff. 
(cm) (95% 

CI)

0.28 (−4.53; 
5.09)

−5.26 
(−10.27; 
−0.26)*

−5.72 
(−7.25; 
−4.18)*

0.03 (−5.75; 
0.64)

−6.33 
(−1.23; 
−0.01)*

−0.69 
(−0.88; 
−0.50)*

0.01 1.73 1.78

Paired ES 
(g) 0.01 0.09 0.1 0.01 0.09 0.1 0.99 (0.98; 

0.99)

0.21 
(−0.200 
0.642)

0.29 
(−1.95; 
0.64)

ICC (95% 
CI)

0.98 (0.97; 
0.99)

0.98 (0.97; 
0.99)

0.99 (0.93; 
0.99)

0.98 (0.97; 
0.99)

0.98 (0.96; 
0.99)

0.99 (0.93; 
0.99)

0.99 (0.96; 
0.99)

0.13 
(0.002; 
0.246)

0.13 
(0.001; 
0.252)

CCC (95% 
CI)

0.97 (0.94; 
0.98)

0.96 (0.92; 
0.98)

0.99 (0.98; 
0.99)

0.97 (0.94; 
0.98)

0.96 (0.92; 
0.98)

0.99 (0.99; 
0.99) - - -

TE (95% 
CI)

1.02 (1.02; 
1.03)

1.02 (1.02; 
1.03)

1.01 (1.01; 
1.02)

1.04 (1.03; 
1.05)

1.04 (1.03; 
1.05)

1.01 (1.01; 
1.02) - - -

CV (95% 
CI) 2 (1.6; 2.6) 2.10 (1.7; 

2.7)
0.70 (0.6; 

0.9) 4 (3.3; 5.2) 4.20 (3.4; 
5.5)

1.30 (1.1; 
1.7) - - -

SWC (cm) 2.89 3 0.93 0.37 0.38 0.11 - - -

Rating Good Good Marginal Marginal Marginal Marginal - - -

* p< 0.05; SJ: Squat Jump; ES: effect size; CI: confidence interval; ICC: intraclass correlation coefficient; TE: typical er-
ror; CV: coefficient of variation; SWC: smallest worthwhile change; (95% CI): Upper and lower confidence intervals.



47 J Global Clinical Engineering Vol.7 Issue 1: 2025

Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

DISCUSSION  

This study had two primary objectives. The first was 
to assess the validity and reliability of the MJ2 app in 
evaluating neuromuscular performance through power 
measurements. The results demonstrated high intra-rater 
reliability (ICC > 0.91) across all studied variables in CMJ 
and SJ, consistent with prior research.25,26 Furthermore, 
mean differences between observers and the contact 
platform for CMJ and SJ (< 0.1 cm) aligned with previous 
findings on MJ2 app validity in both male and female 
participants.23,25,26 Yingling et al.,27 highlighted the necessity 
of establishing confidence in MJ2 due to the potential bias 
introduced by manually selecting take-off and landing 
moments. The present study supports this confidence, as its 
intra-rater reliability findings align with previous research. 
Regarding inter-rater reliability, ICC scores exceeded 0.90 
for flight time and jump height, with CV values below 5%, 
indicating strong reliability.42 These results correspond 
with prior studies on MJ2 reliability.24,26,44,45 Additionally, 
excellent agreement (CCC > 0.95) was found between MJ2 
and the contact platform for both jumps and observers, 
consistent with Bogataj et al.,23 who reported a high level 
of agreement between MJ2 and a photoelectric cell system.

CMJ height exhibited slightly higher variability (CV > 
5%) when compared with the platform, while SJ height 
remained within acceptable limits. These findings contrast 
with previous studies that reported higher CV values 
for MJ2.22,25 Differences in jump type, sample size, and 
equipment used for validation may account for these 
discrepancies.22 For example, studies involving primary 
school children found higher variability in SJ height, likely 
due to a lack of experience executing the movement.13,23 

Regarding test usefulness, as determined by the 
relationship between TE and SWC, flight time was rated 
as good (TE < SWC) for both CMJ and SJ, while jump height 
was rated as marginal (TE > SWC). A comparable study23 
reported similar findings, with a marginal rating for SJ 
height but not for CMJ height.

The primary focus of this study was the assessment of 
neuromuscular performance via peak power estimation 
with MJ2. Results indicated poor reliability (ICC < 0.5) 

when comparing MJ2-derived power measurements with 
those from the contact platform. Conversely, inter-rater 
reliability between observers was high (ICC > 0.98) for 
both jumps. These findings diverge from those of Haynes 
et al.,22 who reported moderate ICC values (ICC = 0.67) 
when assessing mean power in drop jumps. Yingling et 
al.,27 also found good reliability (ICC = 0.85) for peak 
power estimation, highlighting variability across studies. 
In the present study, peak power values obtained from 
the contact platform were lower than those estimated by 
MJ2. This discrepancy may be attributed to differences 
in sampling frequency, as the contact platform records 
at 1,000 Hz, while MJ2 video data is captured at 240 
Hz. These variations in data acquisition may obscure 
crucial details required for accurate power estimation.

Although both MJ2 and the contact platform estimate 
neuromuscular performance via jump height, they employ 
different equations. The contact platform utilized an 
equation proposed by Fox and Mathews,45 whereas MJ2 
applied the Samozino et al.,35 equation, which is more 
recent. Prior studies have reported moderate agreement for 
mean power22 and good agreement for peak power27 when 
evaluating MJ2’s power estimation reliability. Differences 
in reference instruments and potential MJ2 estimation 
errors may explain these discrepancies. Notably, power 
estimation accuracy depends on the precision of jump 
height measurements, as flight time overestimation can 
amplify measurement error due to the squared nature of 
the variable. The disparity in data acquisition rates (1,000 
Hz for the contact platform vs. 240 Hz for MJ2) may also 
contribute to higher flight time and jump height values 
in MJ2 assessments.

 Carlos-Vivas et al.,44 corroborated this observation, 
reporting a slight overestimation of jump height in their 
findings. Even minor overestimations can influence power 
estimation, thereby affecting agreement between MJ2 and 
the contact platform. These findings suggest that accurate 
and reliable force and power measurements require 
direct assessments rather than indirect calculations.

This is the first study to evaluate MJ2’s reliability using 
two devices (tablet and computer) for video analysis. The 
results indicate that manual frame selection is a valid and 



Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

J Global Clinical Engineering Vol.7 Issue 1: 2025 48

reliable method for assessing jump height and flight time, 
regardless of the device used for analysis. This minimizes 
the potential for bias and allows practitioners to use MJ2 
across different screen sizes and environments. The study 
reinforces the reliability of MJ2 for assessing lower-body 
performance, offering a practical solution for practitioners. 

A limitation of this study is the lack of information 
regarding participants’ familiarity with the tested jump 
types. Although participants were active undergraduate 
sports science students, variations in the CMJ technique 
could have influenced the observed variability. Additionally, 
the findings are limited to the study sample and may not be 
generalizable to other populations. Future research should 
further investigate MJ2’s power estimation capabilities by 
incorporating force platforms and alternative vertical jump 
tests (e.g., Abalakov) to enhance agreement, correlation, 
and mean difference assessments. Expanding the sample 
to include more female participants would also improve 
the generalizability of results.

Despite these limitations, the present study supports 
the use of MJ2 to measure jump height and flight time in 
an active young population. The increasing popularity, 
affordability, and technological advancements of 
smartphone applications suggest that tools like MJ2 will 
become integral to assessing physical fitness and health 
metrics.47 These findings contribute to existing literature 
and enhance confidence in MJ2 as a rapid and reliable 
assessment tool for lower-body strength.

CONCLUSIONS

The results of the present study recommend using the 
MJ2 smartphone app as a valid, reliable, and useful tool 
for measuring jump height and flight time in active young 
adults. Due to its simplicity and practicability, it can be 
used by physicians, coaches, and other sports science 

practitioners to assess physical fitness, particularly lower-
body performance.

AUTHOR CONTRIBUTIONS

Conceptualization, A.D. and D.T.; Resourses, M.S. and F.S.; 
Data collection, L.S. and P.M.; Data analysis P.P. and E.S.; 
Writing–Original Draft Preparation, A.D. and D.T; Writing–
Review & Editing, M.E., M.S. and F.S.; Supervision, A.D.

ACKNOWLEDGMENTS

We would like to acknowledge all students who volunteer 
to participate in the present study.

FUNDING

This research received no external funding.

DATA AVAILABILITY STATEMENT

Not applicable.

CONFLICTS OF INTEREST

The authors declare they have no competing interests.

CONSENT FOR PUBLICATION

Written consent was obtained from all participants 
regarding publication of data and/or image, as long as 
the images maintain the anonymity of the participant.

FURTHER DISCLOSURE

Not applicable.



49 J Global Clinical Engineering Vol.7 Issue 1: 2025

Dias, Pires, Santana, Marques, Espada, Santos, Silva, Teixeira: Feasibility and Reliability of the My Jump 2 Smartphone Application 
in Measuring Peak Power, Flight Time and Jump Height in Physically Active Subjects during Two Different Jumping Tasks

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