Evaluation of Foot Kinematics During Endurance Running on Different Surfaces in Real-World Environments

  • Markus Zrenner
  • Christoph Feldner
  • Ulf Jensen
  • Nils RothEmail author
  • Robert Richer
  • Bjoern M. Eskofier
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1028)


Despite the fact that endurance running is an outdoor sport, most studies regarding foot kinematics have been conducted indoors in laboratories due to the stationary measurement equipment. Small and low-cost inertial measurement units (IMU) have proven to be accurate measurement tools for foot kinematics. In this study, we used such IMUs to evaluate the effect of different running surfaces on foot kinematics in a real-world scenario. For data collection, twenty amateur runners ran for at least one kilometer on six different surfaces, which were asphalt, tartan, gravel, bark mulch, grass and trail. From the acquired IMU data, we computed the sole angle, the maximum sole angle velocity, the range of motion in the frontal plane and the maximum pronation velocity for each stride. The results showed that the maximum angular rates as well as the absolute rotations are higher for stiffer and more consistent surfaces like tartan and asphalt.


Wearable sensors Inertial measurement units Running Terrain Foot kinematics 



Bjoern Eskofier gratefully acknowledges the support of the German Research Foundation (DFG) within the framework of the Heisenberg professorship programme (grant 526 number ES 434/8-1).


  1. 1.
    Lee, D.-C., Pate, R.R., Lavie, C.J., Sui, X., Church, T.S., Blair, S.N.: Leisure-time running reduces all-cause and cardiovascular mortality risk. J. Am. Coll. Cardiol. 64(5), 472–481 (2014)CrossRefGoogle Scholar
  2. 2.
    Hoogkamer, W., Kipp, S., Frank, J.H., Farina, E.M., Luo, G., Kram, R.: A comparison of the energetic cost of running in marathon racing shoes. Sports Med. 48(4), 1009–1019 (2018)CrossRefGoogle Scholar
  3. 3.
    Anderson, T.: Biomechanics and running economy. Sports Med. 22(2), 76–89 (1996)CrossRefGoogle Scholar
  4. 4.
    Orchard, J.W., Fricker, P.A., Abud, A.T., Mason, B.R.: Biomechanics of iliotibial band friction syndrome in runners. Am. J. Sports Med. 24(3), 375–379 (1996)CrossRefGoogle Scholar
  5. 5.
    Colyer, S.L., Evans, M., Cosker, D.P., Salo, A.I.T.: A review of the evolution of vision-based motion analysis and the integration of advanced computer vision methods towards developing a markerless system. Sports Med.-Open 4(1), 24 (2018)CrossRefGoogle Scholar
  6. 6.
    Strohrmann, C., Harms, H., Tröster, G., Hensler, S., Müller, R.: Out of the lab and into the woods: kinematic analysis in running using wearable sensors. In: Proceedings of the 13 Annual Conference Ubiquitous Computing, pp. 119–122. ACM (2011)Google Scholar
  7. 7.
    Hardin, E.C., Den Bogert, A.J.V., Hamill, J.: Kinematic adaptations during running: effects of footwear surface and duration. Med. Sci. Sports Exerc. 36(5), 838–844 (2004)CrossRefGoogle Scholar
  8. 8.
    Schuldhaus, D., Kugler, P., Jensenm, U., Eskofier, B., Schlarb, H., Leible, M.: Classification of surfaces and inclinations during outdoor running using shoe-mounted inertial sensors. In: 21st ICPR, pp. 2258–2261. IEEE (2012)Google Scholar
  9. 9.
    Blank, P., Kugler, P., Schlarb, H., Eskofier, B.: A wearable sensor system for sports and fitness applications. In: 19th Annual Conference of the ECSS (2014)Google Scholar
  10. 10.
    Ferraris, F., Grimaldi, U., Parvis, M.: Procedure for effortless in-field calibration of three-axial rate gyro and accelerometers. Sens. Mat. 7(5), 311–330 (1995)Google Scholar
  11. 11.
    Zrenner, M., Ullrich, M., Zobel, P., Jensen, U., Laser, F., Groh, B.H., Duemler, B., Eskofier, B.H.: Kinematic parameter evaluation for the purpose of a wearable running shoe recommendation. In: IEEE Transition BSN (2018)Google Scholar
  12. 12.
    De Wit, B., De Clercq, D., Aerts, P.: Biomechanical analysis of the stance phase during barefoot and shod running. J. Biomech. 33(3), 269–278 (2000)CrossRefGoogle Scholar
  13. 13.
    Skog, I., Handel, P., Nilsson, J.-O., Rantakokko, J.: Zero-velocity detection–an algorithm evaluation. IEEE Trans. Biomed. Eng. 57(11), 2657–2666 (2010)CrossRefGoogle Scholar
  14. 14.
    Larsen, R.J., Marx, M.L.: An Introduction to Mathematical Statistics and its Applications, vol. 2. Prentice-Hall Englewood Cliffs, New Jersey (1986)zbMATHGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Markus Zrenner
    • 1
  • Christoph Feldner
    • 1
  • Ulf Jensen
    • 2
  • Nils Roth
    • 1
    Email author
  • Robert Richer
    • 1
  • Bjoern M. Eskofier
    • 1
  1. 1.Machine Learning and Data Analytics LabFriedrich-Alexander-Universität Erlangen-Nürnberg (FAU)ErlangenGermany
  2. 2.Finance & IT – IT Innovation, adidas AGHerzogenaurachGermany

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