4.1.1.2 Tests Subjects
A group of athletes from the Australian wheelchair rugby Paralympic team volunteered to participate in this study. The group comprised nine male participants between 22 and 42 years in age, and each of them had a significant amount of experience in participating in wheelchair rugby at an elite level. Table 4.1 presents test subject’s characteristics including disability level, sport classification as well as typical weekly training hours.
Table 4.1. Subjects’ data, wheelchair mass and d value
Group Subject Disability level and Classification Age (Yr.) Mass (Kg) Size (m) Training Hours/week Elite experience (Yr.) Chair mass (kg) d value (m) A (Low Pointer) A1 C5 - 1.5 32 71.28 1.82 16 1 17.77 0.69 A2 C6 - 0.5 39 73.77 1.83 16 12 17.15 0.56 A3 C6 - 1.5 36 64.00 1.88 15 3 16.27 0.59 B (Mid Pointer) B1 C6/7 - 2.0 24 87 1.87 10 2 17 0.54 B2 C7 - 2.0 34 71 1.87 15-20 10 17 0.57 B3 C6/7 - 2.0 22 84 1.97 20 4 18 0.55 C (High Pointer)
C1 Spinal neurological disorder - 3.0 42 94.15 1.70 10 15 18.79 0.55
C2 C6/7 Inc - 3.0 23 70.09 1.85 18-20 2 18.94 0.53
C3 C7 Inc - 2.5 40 95.00 1.90 10 16 17.23 0.57
The sport classifications of athletes in this sample group (Table 4.1) range from 0.5 to 3.0 (the full classification range for wheelchair rugby is 0.5 to 3.5). As explained in section 2.2.1 (Chapter 2), the point score classification of athletes is linked to the athlete’s disability level, which also dictates mobility capacity and fitness of the athlete. The higher classification number (3.5) is intended for those athletes who have higher function on court and the lower number (0.5) for those athletes with less function on court. Table 2.1 in Chapter 2 explains some of the characteristics of athlete classifications. Hence, as one of the objectives of this chapter is a comparative assessment of athlete’s performance; the sample group requires athletes to be segmented in smaller groups according to their average capacity levels. Therefore, the sample group will be clustered in the following three main classifications groups as specified in Table 4.1 and below:
• Group A - low pointers: Athletes with sports class categories ranging between 0.5 – 1.5
• Group B - mid pointers: Athletes with sports class categories ranging between 1.5 – 2.5
• Group C - high pointers: Athletes with sports class categories ranging between 2.5 – 3.5
This grouping has been developed based on the approach that was adopted by Mason et al. [73] and Molik et al. [107], with the aim of presenting a performance analysis of the data obtained, and to highlight significant differences between subjects of different sports classifications performing similar wheelchair handling activity. This clustering of athletes ensures that the results are matched against athletes of similar characteristics (upper body range of mobility).
The athletes were fully informed of the research procedures and potential risks and written consent was obtained from all research participants. Ethics approval was obtained from the RMIT University Human Research Ethics Committee before the experimental study being undertaken. For details of Ethics approval please refer to APPENDIX E.
4.1.1.3 Instrumentation
The experimental tests were carried out during a single day session in an indoor basketball court in exactly the same conditions of regular training drills to ensure that the athletes were familiar with the tasks. To allow reporting on the performance of the available sample of athletes, all athletes completed testing using their own custom- built match chairs. The study of experienced athletes’ performance using their own customized equipment is appropriate and highly regarded as the athlete’s wheelchair is considered an extension of the athletes’ body for game rules compliance [68]. All conclusions on performance for the purpose of this study will be based on wheelchair + athlete system as a whole. All test wheelchairs were specifically designed to meet the athletes’ individual anthropometric needs and the mechanical characteristics of all
chairs complied with section four of the International Wheelchair Rugby Federation IWRF rules (International Wheelchair Rugby Federation, 2008).
Each wheelchair was instrumented as shown in Fig. 4.1, with a 6 DOF sensor (accelerometer + gyrometer - MinimaxX, Catapult Innovations Pty Ltd, Scoresby, Australia) at 100Hz sample rate.
Figure 4.1. Instrumental setup on the pick bar of the wheelchair with a 6 DOF accelerometer + gyrometer sensor - minimaxX, Catapult Innovations Pty Ltd, Scoresby, Australia.
m
ay
Due to the limited space available to place and secure the sensor on the wheelchair and since access to the sensor before and after each trial was necessary, the flat surface of the front pick bar of the chair was used. The sensor was aligned with the middle plane of the wheelchair and securely fastened in the upright position (positive z-axis downwards); on which, the positive x-axis of the sensor was directed to the left side of the chair’s forward position (see Fig. 4.1). The sensor’s positive y-axis was positioned on the chair’s sagittal plane in line with the chair’s forward position (see Fig. 4.1).
The sensor measured the linear accelerations and angular velocities along and about the three axes of the orthogonal coordinate system shown in Fig.4.1. According to the manufacturer of the mimimax, Catapult Sports, the inertial sensors in the minimax don’t need to be recalibrated after their factory setting. However, the recalibration process for the accelerometer and gyroscope provided by the manufacturer and available in Appendix A can be performed if desired. Nevertheless, for the purpose of the tests performed in this study, the acceleration readings of each axis were checked against gravitational acceleration (9.81 m/s2); and the three axis angular velocities were checked against known rpm values of a turntable prior to instrumentation of the wheelchair as similarly done for validation of the proposed method (see Appendix B). 4.1.1.4 Data Processing
Original and filtered acceleration data were analysed and percentages of real numbers retrieved were compared. Highest percentages of real numbers were achieved by using original (not filtered) data. Therefore filtering was avoided for obtaining experimental results.
To synchronize stopwatch and accelerometer data, the slight offset of the data at zero acceleration (due to normalizing activity prior to test) was corrected such that ay
(forward/backward acceleration) overlapped the zero acceleration line before evident acceleration activity (start of stopwatch) was initiated. Basic video taken for each trial was used as reference to further understand behaviours in the minimax acceleration data. In particular, the recorded visuals helped identifying the normalising data period, which is comprised by the recorded accelerations from the time when the minimax was switched on up until the ‘go’ command and subsequent first push. Additionally, the straight and turning sections of the Illinois test were identified in the acceleration dataset as peaks in the angular acceleration curve, which correlated with path sections from the video, and time was correlated across stopwatch, video and minimax. Video was taken using a Sony HDR-CX110 high-definition camcorder HDFX 1920x1080 at 60 interlaced frames per second (1080/60i), bit rate 24 Mbps.
Further processing also involved the conversion of angular velocity data about vertical axis from deg/s to rad/s.
The following is the data processing procedure followed to produce the data used for analysis:
1 Record minimax coordinate system selected for the experiment: identify axis to correlate with desired data output from minimax software.
2 Measure and record d of experiment. d=constant distance between accelerometer and wheelchair centre (midpoint between the COPs of the 2 wheels) and is different for each subject depending on the chair.
3 Save minimax raw data output and the corresponding firmware software in a single folder. Run the firmware software to convert the raw file on to a .cvs extension file and save output.
4 Open csv on excel and name acceleration, gyro and time data columns: a (x,y,a) , g (x,y,z) & t - first 6 columns and last from .cvs minimax output.
Note: According to minimax placement for this experiment - Coordinate system: x- left, y-forward, z-downward:
• AX: x = sideward linear acceleration (m/s2) • AY: y = forward/backward acceleration (m/s2)
• GZ: z = ω = angular velocity about vertical axis in deg/s 5 Convert GZ data to rad/s
6 Correct offset for initiation of acceleration activity: To do this, Plot ay (better accuracy) vs. t and find time of first activity on drill (i.e t=12.18s). Then obtain main value from t=0 to t=first activity. Create an offset column for all data (a & g) by subtracting mean value from first row (locked value in cell) on each column.
The three trials for each athlete were averaged and results analysed for linear velocity, and acceleration; these findings were reported for sprinting tests as per the required performance criteria outlined by the athletes in the QFD (Chapter 3). For the agility test, further analysis was performed using the velocity and acceleration data and applying a newly developed method to report on the instantaneous radius and tangential velocity as explained in the following subsections.
The performance data obtained from the nine athletes consisting of 27 experiments is used to develop and validate the necessary methods to obtain the tangential velocity and radius of curvature previously outlined in objectives b), c), and d) stated at the beginning of section 4.1.