An Intelligent System for Motor Style Assessment and Training from Inertial Sensor Data in Intermediate Level Ski Jumping

Heike Brock, Yuji Ohgi

2016

Abstract

In this research we developed a wearable, augmented motion feedback system for ubiquitous training and motion assessment in mid-level ski jumping. Ski jump motion data captured with a set of inertial sensors were first transformed into meaningful kinematic motion information using an extensive processing system. Next, derived segment orientations, joint positions and joint angles were used to build and train motion knowledge on the base of the sport’s common style and judging criteria. This intelligent machine knowledge was then applied to identify specific style information within incoming motion data that could be provided to the athlete as augmented motion feedback via a mobile training application. System validations on a set of test jumping data showed that style errors could be recognized and displayed well by the implemented system. We therefore believe the system to be suitable for the provision of kinematic motion feedback that could not be obtained without an extensive training support environment otherwise. Adding a real-time environment for athlete-system communication, this could lead to the creation of an ubiquitous training support application in future.

References

  1. Bächlin, M., Kusserow, M., Tröster, G., and Gubelmann, H. (2010). Ski jump analysis of an olympic champion with wearable acceleration sensors. In 2010 International Symposium on Wearable Computers (ISWC), pages 1-2. IEEE.
  2. Bulling, A., Blanke, U., and Schiele, B. (2014). A tutorial on human activity recognition using body-worn inertial sensors. ACM Computer Survey, 46(3):33:1- 33:33.
  3. Chardonnens, J., Favre, J., Cuendet, F., Gremion, G., and Aminian, K. (2013). A system to measure the kinematics during the entire ski jump sequence using inertial sensors. Journal of Biomechanics, 46(1):56-62.
  4. Chardonnens, J., Favre, J., Le Callennec, B., Cuendet, F., Gremion, G., and Aminian, K. (2012). Automatic measurement of key ski jumping phases and temporal events with a wearable system. Journal of Sports Sciences, 30(1):53-61.
  5. Dadashi, F., Millet, G., and Aminian, K. (2014). Estimation of front-crawl energy expenditure using wearable inertial measurement units. IEEE Sensors Journal, 14(4):1020-1027.
  6. Euston, M., Coote, P., Mahony, R., Kim, J., and Hamel, T. (2008). A complementary filter for attitude estimation of a fixed-wing uav. In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008. IROS 2008., pages 340-345. IEEE.
  7. FIS (2013). The international ski competition rules (ICR). Book III. Ski jumping.
  8. Ghasemzadeh, H. and Jafari, R. (2011). Coordination analysis of human movements with body sensor networks: A signal processing model to evaluate baseball swings. IEEE Sensors Journal, 11(3):603-610.
  9. Helten, T., Brock, H., Müller, M., and Seidel, H.-P. (2011). Classification of trampoline jumps using inertial sensors. Sports Engineering, 14(2-4):155-164.
  10. Lee, T. J., Zihajehzadeh, S., Loh, D., Hoskinson, R., and Park, E. J. (2015). Automatic jump detection in skiing/snowboarding using head-mounted mems inertial and pressure sensors. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 229(4):278-287.
  11. Li, C., Khan, L., and Prabhakaran, B. (2005). Realtime classification of variable length multi-attribute motions. Knowledge and Information Systems, 10(2):163-183.
  12. Logical Product (2015). Sports sensing 9-axial waterproof inertial sensor (ss-ws1215/ss-ws1216). Accessed 2015-10-17.
  13. Madgwick, S. O., Harrison, A. J., and Vaidyanathan, R. (2011). Estimation of imu and marg orientation using a gradient descent algorithm. In 2011 IEEE International Conference on Rehabilitation Robotics (ICORR), pages 1-7. IEEE.
  14. Marqués-Bruna, P. and Grimshaw, P. (2009a). Mechanics of flight in ski jumping: Aerodynamic stability in pitch. Sports Technology, 2(1-2):24-31.
  15. Marqués-Bruna, P. and Grimshaw, P. (2009b). Mechanics of flight in ski jumping: aerodynamic stability in roll and yaw. Sports Technology, 2(3-4):111-120.
  16. Milosevic, B. and Farella, E. (2015). Wearable inertial sensor for jump performance analysis. In Proceedings of the 2015 Workshop on Wearable Systems and Applications, WearSys 7815, pages 15-20, New York, NY, USA. ACM.
  17. Ohgi, Y., Hirai, N., Murakami, M., and Seo, K. (2009). Aerodynamic study of ski jumping flight based on inertia sensors (171). In The Engineering of Sport 7, pages 157-164. Springer.
  18. Seo, K., Murakami, M., and Yoshida, K. (2004). Optimal flight technique for v-style ski jumping. Sports Engineering, 7(2):97-103.
  19. Yun, X. and Bachmann, E. R. (2006). Design, implementation, and experimental results of a quaternion-based kalman filter for human body motion tracking. IEEE Transactions on Robotics, 22(6):1216-1227.
  20. Yun, X., Bachmann, E. R., and McGhee, R. B. (2008). A simplified quaternion-based algorithm for orientation estimation from earth gravity and magnetic field measurements. IEEE Transactions on Instrumentation and Measurement, 57(3):638-650.
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Paper Citation


in Harvard Style

Brock H. and Ohgi Y. (2016). An Intelligent System for Motor Style Assessment and Training from Inertial Sensor Data in Intermediate Level Ski Jumping . In Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support - Volume 1: icSPORTS, ISBN 978-989-758-205-9, pages 101-108. DOI: 10.5220/0006032901010108


in Bibtex Style

@conference{icsports16,
author={Heike Brock and Yuji Ohgi},
title={An Intelligent System for Motor Style Assessment and Training from Inertial Sensor Data in Intermediate Level Ski Jumping},
booktitle={Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support - Volume 1: icSPORTS,},
year={2016},
pages={101-108},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006032901010108},
isbn={978-989-758-205-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support - Volume 1: icSPORTS,
TI - An Intelligent System for Motor Style Assessment and Training from Inertial Sensor Data in Intermediate Level Ski Jumping
SN - 978-989-758-205-9
AU - Brock H.
AU - Ohgi Y.
PY - 2016
SP - 101
EP - 108
DO - 10.5220/0006032901010108