Literature DB >> 22275617

Velocity-dependent reference trajectory generation for the LOPES gait training robot.

N Tufekciler1, E H F van Asseldonk, H van der Kooij.   

Abstract

The aim of this study is to assess the feasibility of an approach for generating velocity-dependent trajectories to train neurologically injured patients. The reference trajectories are constructed based on the gait patterns of subjects walking on a treadmill. By extracting key events (parameters) from these trajectories, the velocity dependency of the parameters is determined by regression analysis. Then, splines are fitted through these points to obtain gait patterns (position, velocity and acceleration) for specific walking velocities. Considering the severely injured patients, a feedforward controller is used in addition to the impedance controller. The approach is implemented on the LOPES gait rehabilitation robot and evaluated on healthy subjects. Results indicate that the subjects can walk naturally in the robot with the constructed reference trajectories. Further improvements to the technical design and additional testing of healthy and impaired subjects are required to show whether this approach can be transferred to clinical domain.
© 2011 IEEE

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Year:  2011        PMID: 22275617     DOI: 10.1109/ICORR.2011.5975414

Source DB:  PubMed          Journal:  IEEE Int Conf Rehabil Robot        ISSN: 1945-7898


  3 in total

Review 1.  Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now?

Authors:  Rocco Salvatore Calabrò; Alberto Cacciola; Francesco Bertè; Alfredo Manuli; Antonino Leo; Alessia Bramanti; Antonino Naro; Demetrio Milardi; Placido Bramanti
Journal:  Neurol Sci       Date:  2016-01-18       Impact factor: 3.307

Review 2.  Robotics in Lower-Limb Rehabilitation after Stroke.

Authors:  Xue Zhang; Zan Yue; Jing Wang
Journal:  Behav Neurol       Date:  2017-06-08       Impact factor: 3.342

3.  An Adaptable Human-Like Gait Pattern Generator Derived From a Lower Limb Exoskeleton.

Authors:  Rafael Mendoza-Crespo; Diego Torricelli; Joel Carlos Huegel; Jose Luis Gordillo; Jose Luis Pons; Rogelio Soto
Journal:  Front Robot AI       Date:  2019-05-14
  3 in total

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