Research: Analysis of human movement in running
The purpose of our research on running is to challenge and enhance the standard practice. In general, biomechanical running measurements are performed in laboratory environments. In our opinion, this is not an adequate measuring method for observing and capturing running movement. To collect and characterize this movement, several hundred or thousand roll-over patterns of one person may be necessary. Furthermore, human movement in running should be affected as little as possible by scientific measuring systems. These high demands can hardly be fulfilled in a laboratory environment.
The solution of the problem is extremely simple: Why not perform scientific measurements in a natural running environment (for example, in the park, in the forest, on dirt tracks)? There's one catch: at the moment, just a few measuring systems exist which do not disturb either the running movement or the subjective feeling of the runners during measuring. These measuring systems can also acquire only a fraction of what is currently possible in laboratory environment.
Participant during field testing
Inertial sensors on test shoes (prototype)
Industrially produced inertial sensor compared to a 20 cent coin
Nevertheless, substantial technological progress has occurred in this area over the last few years. Inertial sensors are innovative measuring systems in running research. These systems are the size and weight of a matchbox. They include accelerometers, gyrometers, barometers and magnetic field sensors, as well as data storage and an energy supply with Lithium-Polymer (LiPO) batteries. Inertial sensors have the important advantage that they are small and lightweight for biomechanical applications. They consume less energy and don't disturb the movement process. Thereby, continuous measurements are possible in realistic conditions for several hours without cable connections or data transfer to a computer.
Our aim is to develop this new measuring method in running and to generate reference data. Moreover, we want to learn how we can interpret such data, if the data show the fatigue of the runner or if material properties and technologies of running shoes have an influence on data. For this purpose, we analyse the continuous recording of data for several hundred or thousand roll-over patterns to make specific statements about the running movement of the participant. Finally, every participant generates millions of data points during their runs which can be analysed with statistical methods after completion of the measurements.
- Oriwol, D. (2012). Methodologische Aspekte biomechanischer Messungen unter Laborbedingungen. Eine kritische Betrachtung des gängigen Messprotokolls des Ausdauerlaufens. Dissertation, Technische Universität Chemnitz. (Infos)
- Stergiou, N. & Decker, L. M. (2011). Human movement variability, nonlinear dynamics, and pathology: is there a connection? Hum Mov Sci, 30, 869-888.
- Meardon, S. A.; Hamill, J. & Derrick, T. R. (2011). Running injury and stride time variability over a prolonged run. Gait Posture, 33, 36-40.
- Jordan, K.; Challis, J. H. & Newell, K. M. (2006). Long range correlations in the stride interval of running. Gait Posture, 24, 120-125.