Despite the increasing interest in using powered ankle-foot orthoses for assistive purposes, their development and benchmarking still present core challenges. Powered orthoses have to be safe and provide adequate torque while keeping limited size and weight. The discordance of these requirements is a challenge for the development of these devices. This paper describes the control strategy and characterization of a compact variable stiffness actuator, to be used in an assistive ankle-foot orthosis for impaired subjects. The results of the characterization experiments show the advantageous behavior of the actuator and its performance in providing different relevant assistive torque profiles, with different actuator stiffnesses, during emulated walking experiments. However, some divergences in the results obtained in different testing conditions highlight the need for more general benchmarking techniques. Towards this objective, the paper also proposes a novel performance indicator that can be used to better evaluate the performance of robotic actuators both in quasi-static and in dynamic conditions. The article concludes with a call for research on new benchmarking techniques, to understand more in-depth series elastic's actuators behavior under dynamic conditions.

During movements, humans continuously regulate their joint impedance to minimize control effort and optimize performance. Joint impedance describes the relationship between a joint's position and torque acting around the joint. Joint impedance varies with joint angle and muscle activation and differs from trial-to-trial due to inherent variability in the human control system. In this paper, a dedicated time-varying system identification (SI) framework is developed involving a parametric, kernel-based regression, and nonparametric, "skirt decomposition," SI method to monitor the time-varying joint impedance during a force task. Identification was performed on single trials and the estimators included little a priori assumptions regarding the underlying time-varying joint mechanics. During the experiments, six (human) participants used flexion of the wrist to apply a slow sinusoidal torque to the handle of a robotic manipulator, while receiving small position perturbations. Both methods revealed that the sinusoidal change in joint torque by activation of the wrist flexor muscles resulted in a sinusoidal time-varying joint stiffness and resonance frequency. A thirdorder differential equation allowed the parametric kernel-based estimator to explain on average 76% of the variance (range 52%-90%). The nonparametric skirt decomposition method could explain on average 84% of the variance (range 66%-91%). This paper presents a novel framework for identification of timevarying joint impedance by making use of linear time-varying models based on a single trial of data.

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Unifying system identification and biomechanical formulations for the estimation of muscle, tendon and joint stiffness during human movement To cite this article: Christopher P Cop et al 2021 Prog. Biomed. Eng. 3 033002 View the article online for updates and enhancements.

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