The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Design, Implementation, and Experimental Results of a Quaternion-Based Kalman Filter for Human Body Motion Tracking
Abstract
Real-time tracking of human body motion is an important technology in synthetic environments, robotics, and other human-computer interaction applications. This paper presents an extended Kalman filter designed for real-time estimation of the orientation of human limb segments. The filter processes data from small inertial/magnetic sensor modules containing triaxial angular rate sensors, accelerometers, and magnetometers. The filter represents rotation using quaternions rather than Euler angles or axis/angle pairs. Preprocessing of the acceleration and magnetometer measurements using the Quest algorithm produces a computed quaternion input for the filter. This preprocessing reduces the dimension of the state vector and makes the measurement equations linear. Real-time implementation and testing results of the quaternion-based Kalman filter are presented. Experimental results validate the filter design, and show the feasibility of using inertial/magnetic sensor modules for real-time human body motion tracking
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Citations
Cites
Kalman filtering for real-time orientation tracking of handheld microsurgical instrument
Ang, W. T., Khosla, P. K., & Riviere, C. N. (2005) · 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566) · doi:10.1109/iros.2004.1389796 · Cited by 45
Cited by
Stronger, Smarter, Softer: Next-Generation Wearable Robots
Asbeck, A. T., De Rossi, S. M. M., Galiana, I., Ding, Y., & Walsh, C. J. (2014) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2014.2360283 · Cited by 368
Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion
Filippeschi, A., Schmitz, N., Miezal, M., Bleser, G., Ruffaldi, E., & Stricker, D. (2017) · Sensors · doi:10.3390/s17061257 · Cited by 361
Estimating Three-Dimensional Orientation of Human Body Parts by Inertial/Magnetic Sensing
Sabatini, A. M. (2011) · Sensors · doi:10.3390/s110201489 · Cited by 349
An optimization-based approach to human body motion capture using inertial sensors
Kok, M., Hol, J. D., & Schön, T. B. (2014) · IFAC Proceedings Volumes · doi:10.3182/20140824-6-za-1003.02252 · Cited by 131
Upper limb motion tracking with the integration of IMU and Kinect
Tian, Y., Meng, X., Tao, D., Liu, D., & Feng, C. (2015) · Neurocomputing · doi:10.1016/j.neucom.2015.01.071 · Cited by 120
Metadata
- Authors
- Yun, X., & Bachmann, E. R.
- Venue
- IEEE Transactions on Robotics
- Published
- 2006-12
- Volume
- 22
- Issue
- 6
- Pages
- 1216-1227
- ISSN
- 1552-3098 (ISSN-L)
- OpenAlex
- W2040378481
- Cited by
- 569
- References
- 1
- FWCI
- 32.30
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yun, X., & Bachmann, E. R. (2006). Design, Implementation, and Experimental Results of a Quaternion-Based Kalman Filter for Human Body Motion Tracking. IEEE Transactions on Robotics. https://doi.org/10.1109/tro.2006.886270
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