Development of an innovative portable running analysis toolbox
Studying a person's running biomechanics has been limited to a laboratory setting due to the complex, expensive equipment needed to capture their motion and forces. Recent developments in wearable technologies may allow these measurements to be captured outside of the lab, which is not only a cost effective alternative, but may allow for the collection of data in a more "natural" environment. While these wearable sensors may represent the future for assessing a person's running pattern, they need to be compared with the current in-lab, gold-standard approaches to ensure they are valid. In this project, we will collect data on eighty recreational runners in both lab-based and real-world settings using novel wearable technology combined with the gold-standard motion capture and force plate data collection. We will use state-of-the-art machine learning approaches to process the wearable sensor data and compare it with the lab-based measures. This research will be the first of its kind to develop a portable, wearable, minimally-intrusive analysis “toolbox” to assess a person's running biomechanics without the traditional constraints of an indoor lab.