%0 Conference Paper %B 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) %D 2019 %T A real-time identification and tracking method for the musculoskeletal model of human arm %A C. Fang %A A. Ajoudani %A A. Bicchi %A N. G. Tsagarakis %B 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) %G eng %0 Journal Article %J IEEE Robotics and Automation Letters %D 2017 %T Online Model Based Estimation of Complete Joint Stiffness of Human Arm %A C. Fang %A A. Ajoudani %A A. Bicchi %A N. G. Tsagarakis %K Haptics %K Robotics %X

The endpoint stiffness of the human arm has been long recognized as a key component ensuring the quasi-static stability of the arm physical interactions with the external world. Similarly, the understanding of the joint stiffness behavior can provide complementary insights, e.g., on the underlying stiffness regulation principles across different joints including the nullspace stiffness profiles. Traditionally, the experimental modeling and estimation of the human arm joint stiffness is achieved by the transformation of the identified arm endpoint stiffness to the joint coordinates. Due to the underlying kinematic redundancy, the obtained joint stiffness matrix is rank-deficient which implies that the information in the joint stiffness matrix is incomplete. While in robotics applications this issue can be addressed by designing a desired nullspace stiffness behavior through appropriate projections, the use of a similar technique in the identification of human joint stiffness profile is meaningless. Hence, the first objective of this work is to address this issue by developing a novel technique to identify the complete and physiologically meaningful joint stiffness of human arm. Second, we present a model-based online estimation technique to estimate the seven-dimensional complete joint stiffness in various arm poses and activation levels of the two dominant arm muscles that correspond to the geometric and volume modifications of the joint stiffness profile, respectively.

%B IEEE Robotics and Automation Letters %V 3 %P 84 - 91 %8 01/2018 %G eng %U http://ieeexplore.ieee.org/document/7990237/ %N 1 %R 10.1109/LRA.2017.2731524 %0 Conference Paper %B IEEE International Conference of Intelligent Robots and Systems (IROS2017) %D 2017 %T Online Model Based Estimation of Complete Joint Stiffness of Human Arm %A C. Fang %A A. Ajoudani %A A. Bicchi %A N. G. Tsagarakis %K Robotics %B IEEE International Conference of Intelligent Robots and Systems (IROS2017) %C Vancouver, Canada, September 24–28, 2017 %0 Journal Article %J International Journal of Robotics Research %D 2017 %T Reduced-Complexity Representation of the Human Arm Active Endpoint Stiffness for Supervisory Control of Remote Manipulation %A A. Ajoudani %A C. Fang %A N. G. Tsagarakis %A A. Bicchi %B International Journal of Robotics Research %V 37 %8 11/2017 %G eng %U https://journals.sagepub.com/doi/full/10.1177/0278364917744035 %N 1 %& 155 %R https://doi.org/10.1177%2F0278364917744035 %0 Conference Paper %B IEEE International Conference of Intelligent Robots and Systems - IROS2015 %D 2015 %T A Reduced-Complexity Description of Arm Endpoint Stiffness with Applications to Teleimpedance Control %A A. Ajoudani %A C. Fang %A N G Tsagarakis %A A. Bicchi %K Haptics %K Robotics %X

Effective and stable execution of a remote task in an uncertain environment requires that the task force and position trajectories of the slave robot be appropriately commanded. To achieve this goal, in teleimpedance control, a reference command which consists of the stiffness and position profiles of the master is computed and realized by the compliant slave robot in real-time. This highlights the need for a suitable and computationally efficient tracking of the human limb stiffness profile in real-time. In this direction, based on the observations in human neuromotor control which give evidence on the predominant use of the arm configuration in directional adjustments of the endpoint stiffness profile, and the role of muscular co-activations which contribute to a coordinated stiffening of the task stiffness in all directions, we propose a novel and computationally efficient model of the arm endpoint stiffness behaviour. With the purpose of real-time tracking of the human arm kinematics, an arm triangle is introduced using three body markers at the shoulder, elbow and wrist joints. In addition, a co-contraction index is defined using muscular activities of a dominant antagonistic muscle pair. Calibration and identification of the model parameters are carried out experimentally, using perturbation-based arm endpoint stiffness measurements in different arm configurations and co-contraction levels of the chosen muscles. Results of this study suggest that the proposed model enables the master to naturally execute a remote task by modulating the direction of the major axes of the endpoint stiffness and its volume using arm configuration and the co-ativation of the involved muscles, respectively.

%B IEEE International Conference of Intelligent Robots and Systems - IROS2015 %I IEEE %C Hamburg, Germany, 28 Sept - 2 Oct 2015 %P 1017 - 1023 %G english %U http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7353495 %R 10.1109/IROS.2015.7353495