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Open AccessArticle

Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques

1
Dynamic Interaction Control at Istituto Italiano di Tecnologia, Center for Robotics and Intelligent Systems, Via San Quirico 19D, 16163 Genoa, Italy
2
Machine Learning and Optimisation, The University of Manchester, Manchester M13 9PL, UK
3
DIBRIS, University of Genova, 16145 Genova, Italy
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(12), 2794; https://doi.org/10.3390/s19122794
Received: 1 May 2019 / Revised: 15 June 2019 / Accepted: 17 June 2019 / Published: 21 June 2019
(This article belongs to the Special Issue Sensors for Biomechanics Application)
The paper presents a stochastic methodology for the simultaneous floating-base estimation of the human whole-body kinematics and dynamics (i.e., joint torques, internal and external forces). The paper builds upon our former work where a fixed-base formulation had been developed for the human estimation problem. The presented approach is validated by presenting experimental results of a health subject equipped with a wearable motion tracking system and a pair of shoes sensorized with force/torque sensors while performing different motion tasks, e.g., walking on a treadmill. The results show that joint torque estimates obtained by using floating-base and fixed-base approaches match satisfactorily, thus validating the present approach. View Full-Text
Keywords: floating-base dynamics estimation; human joint torque analysis; human wearable dynamics floating-base dynamics estimation; human joint torque analysis; human wearable dynamics
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MDPI and ACS Style

Latella, C.; Traversaro, S.; Ferigo, D.; Tirupachuri, Y.; Rapetti, L.; Andrade Chavez, F.J.; Nori, F.; Pucci, D. Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques. Sensors 2019, 19, 2794.

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