Literature DB >> 20194054

Path control: a method for patient-cooperative robot-aided gait rehabilitation.

Alexander Duschau-Wicke1, Joachim von Zitzewitz, Andrea Caprez, Lars Lunenburger, Robert Riener.   

Abstract

Gait rehabilitation robots are of increasing importance in neurorehabilitation. Conventional devices are often criticized because they are limited to reproducing predefined movement patterns. Research on patient-cooperative control strategies aims at improving robotic behavior. Robots should support patients only as much as needed and stimulate them to produce maximal voluntary efforts. This paper presents a patient-cooperative strategy that allows patients to influence the timing of their leg movements along a physiologically meaningful path. In this "path control" strategy, compliant virtual walls keep the patient's legs within a "tunnel" around the desired spatial path. Additional supportive torques enable patients to move along the path with reduced effort. Graphical feedback provides visual training instructions. The path control strategy was evaluated with 10 healthy subjects and 15 subjects with incomplete spinal cord injury. The spatio-temporal characteristics of recorded kinematic data showed that subjects walked with larger temporal variability with the new strategy. Electromyographic data indicated that subjects were training more actively. A majority of iSCI subjects was able to actively control their gait timing. Thus, the strategy allows patients to train walking while being helped rather than controlled by the robot.

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Year:  2010        PMID: 20194054     DOI: 10.1109/TNSRE.2009.2033061

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  55 in total

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2.  Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules.

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3.  The effects of robot assisted gait training on temporal-spatial characteristics of people with spinal cord injuries: A systematic review.

Authors:  Stephen Clive Hayes; Christopher Richard James Wilcox; Hollie Samantha Forbes White; Natalie Vanicek
Journal:  J Spinal Cord Med       Date:  2018-02-05       Impact factor: 1.985

Review 4.  Neurorobotic and hybrid management of lower limb motor disorders: a review.

Authors:  Juan C Moreno; Antonio J Del Ama; Ana de Los Reyes-Guzmán; Angel Gil-Agudo; Ramón Ceres; José L Pons
Journal:  Med Biol Eng Comput       Date:  2011-08-17       Impact factor: 2.602

5.  Oscillator-based assistance of cyclical movements: model-based and model-free approaches.

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Journal:  Med Biol Eng Comput       Date:  2011-09-01       Impact factor: 2.602

6.  Estimating the Mechanical Behavior of the Knee Joint During Crouch Gait: Implications for Real-Time Motor Control of Robotic Knee Orthoses.

Authors:  Zachary F Lerner; Diane L Damiano; Thomas C Bulea
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2016-04-14       Impact factor: 3.802

Review 7.  Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review.

Authors:  Roland Sigrist; Georg Rauter; Robert Riener; Peter Wolf
Journal:  Psychon Bull Rev       Date:  2013-02

8.  The effect of haptic guidance and visual feedback on learning a complex tennis task.

Authors:  Laura Marchal-Crespo; Mark van Raai; Georg Rauter; Peter Wolf; Robert Riener
Journal:  Exp Brain Res       Date:  2013-09-08       Impact factor: 1.972

9.  Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training.

Authors:  Alexander Duschau-Wicke; Andrea Caprez; Robert Riener
Journal:  J Neuroeng Rehabil       Date:  2010-09-10       Impact factor: 4.262

10.  Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.

Authors:  Shraddha Srivastava; Pei-Chun Kao; Seok Hun Kim; Paul Stegall; Damiano Zanotto; Jill S Higginson; Sunil K Agrawal; John P Scholz
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2014-10-13       Impact factor: 3.802

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