The information presented on this homepage is based on one or more of the following academic references. You can find a detailed description of all methods presented on this website and their complete mathematics in the listed publications.
All information published on his homepage is inspired by the contents of my PhD thesis. Essential parts are furthermore illustrated in the following publications of which I was the main or a contributing author.
- Brock, H. and Ohgi, Y. Intelligent Drift Reduction in Inertial Sensor Orientation Estimates Using Elementary Motion Knowledge. KEIO SFC Journal, Vol.16, No. 1, pp. 170-203, 2016.
- Brock, H. and Ohgi, Y. Development of an inertial motion capture system for kinematic analysis of ski jumping. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 2016.
- Brock, H. and Ohgi, Y. System and Feature Engineering for Automated Style Error Recognition from Wearable Motion Sensor Data. Information, 2016.
- Vinken, P.M., Kröger, D., Fehse, U., Schmitz, G., Brock, H. and Effenberg, A.O. Auditory coding of human movement kinematics. Multisensory research, 26(6):533– 552, 2013
- Helten, T., Brock, H., Müller, M. and Seidel, H.P. Classification of trampoline jumps using inertial sensors. Sports Engineering, 14(2-4):155–164, 2011.
- Brock, H., Schmitz, G., Baumann, J. and Effenberg, A.O., 2012. If motion sounds: Movement sonification based on inertial sensor data. Procedia Engineering, 34, pp.556-561.
- Brock, H. and Ohgi, Y., 2016. Towards better measurability-IMU-based feature extractors for motion performance evaluation. In Proceedings of the 10th International Symposium on Computer Science in Sports (ISCSS) (pp. 109-116). Springer International Publishing.
- Brock, H., Ohgi, Y. and Seo, K., 2016. Development of an Automated Motion Evaluation System from Wearable Sensor Devices for Ski Jumping. Procedia Engineering, 147, pp.694-699.
- Brock, H. and Ohgi, Y.,2016. A visual feedback system for full-body motion analysis from inertial sensor data. Journal of Fitness Research, 5, 34-36.
- Brock, H. and Ohgi, Y.,2016. An Intelligent System for Motor Style Assessment and Training from Inertial Sensor Data in Intermediate Level Ski Jumping. To be published under the Proceedings of the icSports 2016 (INSTICC).
Other important references:
Methodologies and technologies referenced on this homepage are based on the following publications (listed in alphabetical order).
 James Diebel. Representing attitude: Euler angles, unit quaternions, and rotation vectors, 2006.
 S.O.H. Madgwick, A.J.L. Harrison, and R. Vaidyanathan. Estimation of imu and marg orientation using a gradient descent algorithm. In 2011 IEEE International Conference on Rehabilitation Robotics (ICORR), pages 1–7, June 2011.
 R.Mahony, T. Hamel, and Jean-Michel Pflimlin. Nonlinear complementary filters on the special orthogonal group. IEEE Transactions on Automatic Control, 53(5):1203–1218, June 2008.
 J.L.Marins, X. Yun, E.R. Bachmann, R.B.McGhee, and M.J. Zyda. An extended kalman filter for quaternion-based orientation estimation using marg sensors. In 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, Proceedings. Volume 4, pages 2003–2011, 2001.
 X. Yun, E.R. Bachmann, and R.B. McGhee. 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,March 2008.