Countermovement Jump

Figure 3.2: Medial-lateral sway during LOS test

The mobile health support was also provided with sound feedback to guide the subject to maintain balance with respect to an initial position. Sound feedback was set so that an increase in the frequency corresponds to an increase in the distance with respect to the initial position. In this way, the athlete can recognize if he can maintain a given posture after an injury at the lower limbs or if the total functional abilities have not been recovered yet.

height by using the physical formula of motion in free-fall that takes into account the time spent in air by the jumper. Furthermore, the commercial application calculates the height, flight time, velocity, force and power of the vertical jumps. MyJump2 showed to have a good agreement in measures of jump height with compared to force platform data in terms of Pearson’s product-moment correlation coefficient (r = 0.80). One of the limitations of this application is having to necessarily be assisted during the jump. A second person, in fact, has to record the performance and the individual cannot be able to do it alone.

To test the concurrent validity of the mobile health tool, Pearson’s product-moment correlation coefficient (r) was performed. It is a measure of the linear correlation between two variables X and Y. According to the Cauchy–Schwarz inequality, the coefficient has a value between +1 and -1, where 1 is a total positive linear correlation, 0 is no linear correlation, and -1 is the opposite of 1. Pearson’s correlation coefficient, when applied to a sample, is commonly represented by equation 3.3 and may be referred to as the sample correlation coefficient.

r_xy =

qn

i=1(x_i− ˆx)(y_i− ˆy)

ñqn

i=1(x_i− ˆx)^2ñqn_i=1(y_i− ˆy)²

(3.3) In Equation 3.3, n is the sample size, x and y are the individual sample points and ˆx,ˆy are the sample mean. Ten repetitions of countermovement jump were performed with the mobile health tool attached with a belt at the height of the centre of mass. At the same time, the individual repetitions were recorded with the MyJump2 and the instants of take-off and landing were identified by following the procedure explained in the commercial application. Ten heights obtained from the two different instruments were gathered, matched and Pearson’s correlation coefficient has shown a correlation equal to 0.57 between them.

Table 3.1 shows the comparison between the mobile health tool and MyJump2 in evaluating the flight time and the height during a vertical jump. Outcomes show that flight times and heights calculated with the mobile health tool over-estimate the ones evaluated with the MyJump2 application. For the flight time, an average overestimation of 0.038 seconds is shown with a standard deviation of 0.015. Height, instead, is overestimated with a mean of 3.58 centimeters and a standard deviation of 1.40. Figures 3.3 and 3.4 show the flight times and the heights calculated with the mobile health tool (blue line) and MyJump2 (red line) application respectively. As it is clear, both the calculations performed with the mobile health tool are overestimated with respect to the ones evaluated with the commercial application.

Countermovement Jump

Mobile health tool MyJump2

Flight Time[ms] Height[cm] Flight Time[ms] Height[cm]

1 409 20.59 354 15.38

2 400 19.60 346 14.67

3 409 20.59 350 15.02

4 401 19.68 354 15.38

5 430 22.8 400 19.62

6 411 20.69 375 17.24

7 380 17.68 358 15.75

8 382 17.87 354 15.38

9 382 17.87 371 16.86

10 392 18.82 350 15.02

Table 3.1: Countermovement Jump: comparison between the Mobile Health tool and MyJump2 in evaluating flight time and height

Figure 3.3: Flight time calculated with the mobile health tool compared to MyJump2 evaluation

From the moment that the searches made on MyJump2 showed a correlation with force platform equal to 0.8, but did not indicate whether the maximum height during the jump overestimated or underestimated those of the gold standard, it cannot be stated with certainty which of the two are closer to reality.

It was necessary to perform another test to conclude if the mobile health tool gives reasonable results in evaluating the height during a countermovement jump. A system that recorded the jumper while it performed the jump with the smartphone attached to the body was built. Two cameras were placed: one at feet height and one at the location of the head. Moreover, a meter tool was been attached to the wall to observe the displacement of the head with respect

Figure 3.4: Height calculated with the mobile health tool compared to MyJump2 evaluation

to the initial position. Camera placed at the height of feet allowed to identify take-off and landing instants. The one placed at head height allowed to observe how much was the maximum movement achieved during the jump. Looking at the camera placed at head height, in fact, from the empirical research it was deduced that the data calculated with the mobile health tool came closer to reality, compared to those obtained by MyJump2. This result, although interesting, is to be considered subject to observation errors.

Furthermore, the obtained flight times from the smartphone - calculated as explained in Section 2.2.3 - were compared with the ones obtained from the recorded videos. The videos were processed with a video-editing program to identify the exactly instants for take-off and landing by extracting the elapsed time between the frames which identified the two before mentioned moments.

A total of 5 vertical jump repetitions were made and Table 3.2 shows the percentage of error between the flight times evaluated with the two different systems.

Countermovement Jump: percentage error

1st jump 2nd jump 3rd jump 4th jump 5th jump

0% 0.2% 1.5% 0.8% 1.2%

Table 3.2: Countermovement Jump: comparison between the flight times calculated with the Mobile Health tool and the ones calculated from recorded video

The low percentage error shows a great agreement between the mobile health support and the built video-system in evaluating the flight time and, subsequently, in calculating the maximum height reached by the jumper during the countermovement jump.

It can be concluded that, despite the assumption that the body configuration is the same at the instant of take-off and landing, the chosen threshold for detecting the jump event can identify the flight time with reasonable precision if compared to the built video-system.