Identification of Human Limb Stiffness in 5 DoF and Estimation via EMG
To approach robustness and optimal performance, biological musculoskeletal systems can adapt their impedance while interacting with their environment. This property has motivated modern robotic designs including variable-impedance actuators and control methods, based on the capability to vary visco-elastic properties actively or passively. Even though variable-impedance actuation and impedance control in robotics is resolved to a great part, a general set of rules by which impedance is adjusted related to the task at hand is still lacking. This paper aims to fill this gap by providing a method to estimate the stiffness of the human arm in more than two degrees of freedom by perturbation. To overcome ill-conditionedness of the impedance and inertial matrices, we propose and validate methods to separately identify inertial and stiffness parameters. Finally, a model is proposed to estimate the joint stiffness from EMG-measurements of muscle activities.
KeywordsInverse Kinematic Impedance Parameter Inertial Parameter Torque Sensor Human Limb
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- 5.Gomi, H., Osu, R.: Task-dependent viscoelasticity of human multijoint arm and its spatial characteristics for interaction with environments. The Journal of Neuroscience 18, 8965–8978 (1998)Google Scholar
- 7.Lakatos, D., Petit, F., van der Smagt, P.: Conditioning vs. excitation time for estimating impedance parameters of the human arm. IEEE Humanoids (2011)Google Scholar
- 8.Mussa-Ivaldi, F.A., Hogan, N., Bizzi, E.: Neural, mechanical, and geometric factors subserving arm posture in humans. The Journal of Neuroscience 5, 2732–2743 (1985)Google Scholar
- 9.Ngiam, J., Koh, P.W., Chen, Z., Bhaskar, S., Ng, A.: Sparse filtering. In: Shawe-Taylor, J., Zemel, R., Bartlett, P., Pereira, F., Weinberger, K. (eds.) Advances in Neural Information Processing Systems 24, pp. 1125–1133 (2011)Google Scholar