bioRxiv Science⌕ Search

Biology subjects

Nasiri, R.

Publications and source records attributed to Nasiri, R..

3 recordsLinked to original sources

Online Reference Trajectory Adaptation: A Personalized Control Strategy for Lower Limb Exoskeletons

This paper presents a novel method for reference trajectory adaptation in lower limb rehabilitation exoskeletons during walking. Our adaptation rule is extracted from a cost function that penalizes both interaction force and trajectory modification. By adding trajectory modification term into the cost function, we restrict the boundaries of the reference trajectory adaptation according to the patients motor capacity. The performance of the proposed adaptation method is studied analytically in terms of convergence and optimality. We also developed a realistic dynamic walking simulator and utilized it in performance analysis of the presented method. The proposed trajectory adaptation technique guarantees convergence to a stable, reliable, and rhythmic reference trajectory with no prior knowledge about the human intended motion. Our simulations demonstrate the convergence of exoskeleton trajectories to those of simulated healthy subjects while the exoskeleton trajectories adapt less to the trajectories of patients with reduced motor capacity (less reliable trajectories). Furthermore, the gait stability and spatiotemporal parameters such as step time symmetry and minimum toe off clearance enhanced by the adaptation in all subjects. The presented mathematical analysis and simulation results show the applicability and effectiveness of the proposed method and its potential to be applied for trajectory adaptation in lower limb rehabilitation exoskeletons.

bioengineering↗

Human-in-the-Loop Weight Compensation and Mass Estimation in Upper Limb Wearable Robots Towards Muscles Effort Minimization

In this paper: (1) We present a novel human-in-the-loop adaptation method for whole arm muscles effort minimization by means of weight compensation in the face of an object with an unknown mass. (2) This adaptation rule can also be used as a cognitive model for the identification of mass value using EMG sensors. (3) This adaptation rule utilizes the activation (myoelectric) signal of only four muscles in the upper limb to minimize the whole muscles effort. We analytically discuss the stability, optimality, and convergence of the proposed method. The effectiveness of this method for whole muscles effort reduction is studied by simulations (OpenSim software) on a generic and realistic model of the human arm, a model with 7-DOF and 50 Hill-type-muscles. The simulation results show the presented methods performance and applicability for weight compensation and mass estimation in upper limb assistive robots. In addition, the simulations in OpenSim completely support that the suggested set of mono-articular muscles are sufficient for whole muscles effort reduction.

bioengineering↗

A Kinematic Index for Estimation of Metabolic Rate Reduction in Running with I-RUN

In this paper, we target multiple goals related to our passive running assistive device, called I-RUN. The major goals are: (1) finding the main reason behind individual differences in benefiting from our assistive device at the muscles level, (2) devising a simple measure for on-line I-RUN stiffness tuning, and creating a lab-free simple kinematic measure for (3) estimating metabolic rate reduction as well as (4) training subjects to maximize their benefit from I-RUN. Our approach is using some extensive data-driven OpenSim simulation results employing a generic lower limb model with 92-muscles and 29-DOF. It is observed that there is a significant relation between the hip joints kinematic and changes in the metabolic rate in the presence of I-RUN. Accordingly, a simple kinematic index is devised to estimate metabolic rate reduction. This index not only explains individual differences in metabolic rate reduction but also provides a quantitative measure for training subjects to maximize their benefits from I-RUN. The simulation results also re-confirm our hypothesis that "reducing the forces of two antagonistic mono-articular muscles is sufficient for involved muscles total effort reduction". Consequently, we introduce a two-muscles EMG-based metric for the on-line tuning of I-RUN.

bioengineering↗