“Kleist”: Ideas for new parameter to measure running style
- Published
- Accepted
- Subject Areas
- Bioengineering, Bioinformatics, Anatomy and Physiology, Orthopedics, Computational Science
- Keywords
- Running style, "Kleist", Accelerometer
- Copyright
- © 2015 Daumer et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. “Kleist”: Ideas for new parameter to measure running style. PeerJ PrePrints 3:e976v1 https://doi.org/10.7287/peerj.preprints.976v1
Abstract
Many people prefer running to keep in shape. In recent years many self-tracking and self-optimization gadgets has become popular especially for running. We are interested in the quality of running because individual running style has an impact on the running performance as well as on the running injury risk. Hence, in order to increase the performance and lower the injury risk, runners should be educated towards a healthy running technique. Before making an advice, it is crucial to distinguish between different running styles.
Author Comment
The goal is to evaluate the possibility for a running style app using accelerometer data, which is able to track and display the user’s current running style by using accelerometer data, based on which advice can be given for a healthy and efficient running style. Another field of application is purchase advise for running shoes. The feature “Kleist” could be used to find shoes with optimal damping for a runner. This preprint is part of the PeerJ “Human Motion Project” collection (The 2nd Winter Symposium of the Human Motion Project).