Literature DB >> 32746036

Cable-Driven Robotic Interface for Lower Limb Neuromechanics Identification.

Hsien-Yung Huang, Ildar Farkhatdinov, Arash Arami, Mohamed Bouri, Etienne Burdet.   

Abstract

This paper presents a versatile cable-driven robotic interface to investigate the single-joint joint neuromechanics of the hip, knee and ankle in the sagittal plane. This endpoint-based interface offers highly dynamic interaction and accurate position control (as is typically required for neuromechanics identification), and provides measurements of position, interaction force and electromyography (EMG) of leg muscles. It can be used with the subject upright, corresponding to a natural posture during walking or standing, and does not impose kinematic constraints on a joint, in contrast to existing interfaces. Mechanical evaluations demonstrated that the interface yields a rigidity above 500 N/m with low viscosity. Tests with a rigid dummy leg and linear springs show that it can identify the mechanical impedance of a limb accurately. A smooth perturbation is developed and tested with a human subject, which can be used to estimate the hip neuromechanics.

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Year:  2021        PMID: 32746036     DOI: 10.1109/TBME.2020.3004491

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  1 in total

1.  Design, characterisation and validation of a haptic interface based on twisted string actuation.

Authors:  Valeria Skvortsova; Simeon Nedelchev; Joshua Brown; Ildar Farkhatdinov; Igor Gaponov
Journal:  Front Robot AI       Date:  2022-09-16
  1 in total

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