A comparison of alternative motion capture systems for postural measurement of rugby union scrums : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering (Mechatronics) at Massey University, Manawatū, New Zealand

Abstract

Much research has recently been published on the optimal posture in rugby union scrums. These use expensive motion capture systems to collect postural data during trials. There is a clear gap in technology between what is used for training purposes and what is used for research, with the latter being expensive and requiring lengthy calibration times. The method proposed here would remove these as issues to postural data collection by teams using their scrum machines. The method uses a neural network to infer posture from simple a motion capture system that uses inexpensive sensors to return postural parameters such as the angles of the back, as well as the hip, knee, and ankle joints. The accuracy and precision of this method are compared to a commercial motion capture system. The results show that the proposed method performs well compared to the motion capture system and is a suitable method for this type of application. Thus, a clear path for the future development of an instrumented scrum machine that incorporates the capture of postural angles.