The Efficacy of Utilising a GPS-based Inertial Measurement Unit to Conduct Biomechanical Analysis During Running

Biomechanical analysis offers detailed insight into an individual’s movement strategies. Spatiotemporal variables, segmental peak accelerations and joint kinematics are variables that have been linked to predictors of athletic performance and injury risk. Their inclusion within the monitoring frameworks of team sports athletes could further add to the assessment of an athlete’s response to training load and aid in establishing an athlete’s physical condition. Therefore, the aim of this thesis was to investigate the capabilities of a Global Positioning System (GPS) based Inertial Measurement Unit (IMU) to measure the running biomechanical variables that can be used within the context of athlete monitoring frameworks.

The first study focused on accurately identifying foot stance characteristics to calculate spatiotemporal variables of running (Chapter 3). Accuracy was running speed dependant and potentially influenced by an individual’s running style on the acceleration profile of the GPSbased IMU. To understand this further, an investigation was conducted into the effects of running kinematics on the peak accelerations captured by the GPS-based IMUs (Chapter 4). Results showed that the peak velocities of body segments had, on average, a greater effect than the joint/segment angles. More specifically, the peak velocities of the shank and pelvis during the impact subphase of the foot stance had the largest effect on the resultant peak accelerations captured by the GPS devices. Considering the strengths of these relationships found, a method is developed within Chapter 5 where artificial neural networks (ANN) were utilised to predict running kinematics from GPS-based IMU, anthropometric and running speed data. It was found that sagittal plane kinematics of the trunk, pelvis, hip, thigh and knee could all be estimated with different levels of accuracy.

In this thesis, a series of novel methods to conduct biomechanical analysis of running was developed with GPS devices commonly used by team sports athletes. These newly developed data processing and analysis techniques lay the foundations for increasing the biomechanical understanding of athletes in the field concerning sports performance and injury occurrence.