A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification

V. Bonnet, G. Daune, V. Joukov, R. Dumas, P. Fraisse, D. Kulic, A. Seilles, S. Andary, G. Venture

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

6 Citations (Scopus)


This paper presents a method for the real-Time determination of joint angles, velocities, accelerations and joint torques of a human. The proposed method is based on a constrained Extended Kalman Filter that combines stereophotogrammetric and dynamometric data. In addition to the joint variables, subject-specific segment lengths and inertial parameters are identified. Constraints are added to the filter, by restricting the optimal Kalman gain, in order to obtain physically consistent parameters. An optimal tuning procedure of the filter's gains and a sensitivity analysis is presented. The method is validated in the plane on four human subjects and shows very good tracking of skin markers with a RMS difference lower than 15 mm. External ground reaction forces and resultant moment are also accurately estimated with an RMS difference below 3 N and 6 N.m, respectively.

Original languageEnglish
Title of host publication2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016)
EditorsA. Bezerianos, H.I. Krebs, S.L. Kukreja
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781509032877
ISBN (Print)9781509032884
Publication statusPublished - 2016
Externally publishedYes
EventInternational Conference on Biomedical Robotics and Biomechatronics 2016 - National University of Singapore, University Town, Singapore
Duration: 26 Jun 201629 Jun 2016
Conference number: 6th


ConferenceInternational Conference on Biomedical Robotics and Biomechatronics 2016
Abbreviated titleBioRob 2016
CityUniversity Town

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