A Comparison of the Movement Patterns of Specific Rugby Union

Movements on Both Natural Turf and Artificial Turf

S. O’Keeffe

, K. Fullam

, M. O. Feeley

, B. Caulfield

2,3

, E. Delahunt

G. Coughlan

and M. D. Gilchrist

School of Mechanical & Materials Engineering, University College Dublin, Dublin, Ireland

School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Ireland

Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland

Irish Rugby Football Union, Dublin, Ireland

1 INTRODUCTION

A limitation of sports kinematic studies is that they

cannot fully represent in-situ play conditions for fast

dynamic sports. This paper describes the use of new

inertial sensor measurement technology (O’Donovan

et al., 2009) to analyse player motions in the field

under game-like conditions in order to quantify the

impact of different playing surfaces on movement

patterns. The wireless sensor system used in this

study (Shimmer 3, Shimmer Research, Ireland) is a

lightweight (50x25x12.5mm

), wearable, low-power

consumption inertial measurement unit that contains

a tri-axial accelerometer, gyroscope, and

magnetometer. Sensor data can be used to derive a

range of spatiotemporal and kinematic variables to

quantify performance during gait and other

functional activities. In our research we are using

these sensors as a means to characterise movement

during a running activity. The motivation for this

study has been to compare movement profiles and

strategies of rugby players performing game related

tasks on natural turf surfaces and on synthetic

surfaces, to enable a better understanding of the

impact of different playing surfaces on movement

and associated forces and stresses exerted on the

body. This is important as there is a growing trend

towards use of synthetic surfaces in rugby union and

there have been anecdotal reports of injuries that are

perceived to be related to the playing surface. In this

paper we present preliminary movement data

acquired from players performing a 10m sprint test

on natural and synthetic surfaces and describe our

methods of data extraction and subsequent data

processing.

2 METHODS

Twenty elite rugby union players participated

voluntarily. Data were captured from the participants

while they performed running trials on both natural

and synthetic turf playing surfaces. The specific test

carried out was a 10m sprint, which is a standard test

used for quantifying linear acceleration in rugby

union (Duthie et al, 2006). Sensors placed on the

thigh, shank and foot provided data from foot-strike

events for subsequent analysis. All post processing

and analysis was carried out using MATLAB.

Accelerometer and gyroscopic data were calibrated

using 9-DOF calibration Shimmer software and

were low-pass filtered with a zero-phase 5

order

Butterworth filter with 50 Hz and 20 Hz corner

frequencies. Acceleration and angular velocity

vectors were derived with respect to each segment’s

coordinate axes. In this paper, we limit our scope to

consideration of the process of data extraction and

analysis for the data relating to the 10m sprint.

Using the gyroscopic data, the parameters of

sprinting (foot-strike points) from each motion were

successfully identified using the method described

by McGrath et al. (2012), where the stride time is

given as the time between two successive foot -

strikes. These characteristic points successfully

allowed stride time, ST, to be calculated by:

ST(k) = FS(k+1) – FS(k) (1)

where k is the number of cycles, and FS is foot-

strike.

3 RESULTS

A typical sample of the angular velocity data about

the sagittal plane that was measured at the left foot

O’Keeffe S., Fullam K., O. Feeley M., Caulﬁeld B., Delahunt E., Coughlan G. and D. Gilchrist M..

A Comparison of the Movement Patterns of Speciﬁc Rugby Union Movements on Both Natural Turf and Artiﬁcial Turf.

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

during the 10m sprint in trials on both artificial turf

and natural turf is shown below in Figure 1. Figure 2

shows the corresponding resultant of linear

accelerations.

Figure 1: Angular velocity at the left foot about the sagittal

plane during the 10m sprint.

Figure 2: Resultant linear acceleration at the left foot

during the 10m sprint.

From the resultant acceleration data demonstrated in

Figure 2, it can be noted that accelerations

experienced in the first full stride are quite different

to the accelerations experienced in the second full

stride. The first three maxima of resultant linear

accelerations increase significantly with each

progressive maximum. The magnitude of the second

three maxima seems to plateau at around 110 m/s

This shows that during the first stride the participant

is accelerating while during the second stride the

participant is starting to come to steady state and run

at maximum velocity. Taking this into account the

results from the first ‘acceleration stride’ can

usefully be presented in tabular format separately

from the second stride in which the participants

approach steady state.

Table 1: Means, standard deviations and percentage

differences of stride times measured at the left foot and

collected on both artificial and natural turf while doing the

10m sprint. Values are expressed as mean±SD.

Stride Artificial

Turf

(s)

Natural

Turf

(s)

Percentage

Difference

(%)

1 0.485 ±

0.046

0.478 ±

0.034

1.355 ± 5.36

2 0.458 ±

0.035

0.458 ±

0.035

0.15 ± 3.16

In Table 1, Stride 1 refers to the acceleration stride

while Stride 2 refers to the stride that approaches

steady state. The stride times are given in seconds.

The percentage difference is the difference between

corresponding stride times measured on both

surfaces, expressed as a percentage of the stride time

measured on natural turf. The difference between the

corresponding stride times on both surfaces is shown

to be insignificant as the application of a paired T

test for means generated P values that were greater

than 0.05 (for Stride 1, P = 0.33; for Stride 2, P =

0.9)

In Table 2 Maximum 1 refers to the first maximum

of the resultant linear acceleration recorded during

the course of the 10m sprint. In total, 6 maxima of

resultant linear accelerations were recorded during

the course of the test. The percentage difference is

the difference between corresponding maxima of

resultant accelerations measured on both surfaces,

expressed as a percentage of the maximum measured

on natural turf. The difference between the

corresponding maxima of resultant linear

acceleration measured on both surfaces is deemed

insignificant since application of a paired T test for

means generated P values for all six maxima that

were also greater than 0.05 (Maximum 1: P = 0.577,

Maximum 2: P = 0.054, Maximum 3: P = 0.35,

Maximum 4: P = 0.062, Maximum 5: P = 0.44,

Maximum 6: P = 0.2).

Table 2: Means, standard deviations and percentage

differences of maxima of resultant linear accelerations

times measured at the left foot and collected on both

artificial and natural turf while doing the 10m sprint.

Values are expressed as mean±SD.

Maximum Artificial Turf

(m/s

)

Natural Turf

(m/s

)

Percentage

Difference (%)

1 55.62 ± 6.48 54.68 ± 9.89 5.25 ± 24.03

2 89.61 ± 8.48 85.8 ± 10.68 5.15 ± 8.9

3 83.85 ± 11 80.65 ± 18.69 14.68 ± 53 .66

4 115.4 ± 10.2 108.36 ± 13.71 8.09 ± 16.25

5 99.31 ± 9.65 101.47 ± 12.02 -1.34 ± 10.26

6 126.6 ± 10.3 122 ± 14.499 4.94 ± 12.7

0.8 1 1.2 1.4 1.6 1.8 2 2.2 2. 4 2. 6

-20

-15

-10

-5

Time (s)

Angular Velocity (rad/s)

artificial turf

natural turf

Footstrike

1.2 1.4 1.6 1.8 2 2.2 2.4 2.6

100

120

Time (s)

Acceleration (m/s

)

artificial turf

natural turf

Maximum

4 DISCUSSION

On observation of the data, different participants

appeared to display slightly different strategies to

each other when carrying out the test, but the same

participants displayed the same strategy on different

surfaces. This enables a comparison of one surface

to another. The local minima identified in the

angular velocity about the sagittal plane (Figure 1)

indicate points of initial contact or foot strike (FS).

Analysis of this data for all the test participants

showed that each participant completed three clearly

identifiable foot strikes during the 10m sprint.

Equation (1) shows that each participant completed

two full strides in the test. Overall the difference

between stride times on both surfaces was very

small, which was as expected. The largest average

difference between stride times that was measured

was 0.0076 s at the left thigh.

The resultant acceleration data for the 10m sprint

was analysed by comparing the magnitudes of the

corresponding maxima measured on both surfaces.

In general, the difference between the maximum

points of resultant acceleration measured on

artificial turf and natural was not large: the largest

average difference was 4.5m/s

for the third

maximum point recorded at the left foot.

5 CONCLUSIONS

From the results presented, it has been shown that

there is an insignificant difference between the

angular velocity data and the resultant linear

acceleration data collected on both surfaces. This

would indicate that there is no significant difference

in the movement pattern when carrying out a 10m

sprint on artificial turf and on natural turf.

6 FUTURE WORK

It is intended to carry out tests that incorporate

braking and change of direction in order to identify

events of interest associated with these movements.

ACKNOWLEDGEMENTS

Funding from the International Rugby Board, the

Irish Rugby Football Union and Science in Sport is

gratefully acknowledged.

REFERENCES

O’Donovan, KJ; Greene, BR; McGrath, D; O’Neill, R;

Burns, A; Caulfield, B; Shimmer: A new tool for

temporal gait analysis, Annual International

Conference of the IEEE, September 2-6, 2009,

Minneapolis, Minnesota, USA.

Duthie, GM; Pyne, DB; Ross, AA; Livingstone, SG;

Hooper, SL; The reliability of ten-meter sprint time

using different starting techniques, Journal of Strength

and Conditioning Research, 2006, 20(2), 246–251

McGrath, D; Greene, BR; O’Donovan, KJ; Caulfield, B;

Gyroscope based assessment of temporal gait

parameters during treadmill walking and running,

Journal of Sports Engineering, 2012, 15(4), pp. 207-

213.

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