Robotic Orthosis Lokomat: A Rehabilitation and Research Tool
Robotic Orthosis Lokomat: A Rehabilitation and Research Tool
Issue online:
16 Jun 2003
To cite this article: Saˆo Jezernik PhD, Gery Colombo PhD, Thierry Keller PhD, Hansruedi Frueh PhD, Manfred Morari PhD (2003)
Robotic Orthosis Lokomat: A Rehabilitation and Research Tool
Neuromodulation 6 (2), 108Ò115.
doi:10.1046/j.1525-1403.2003.03017.x
Blackwell Synergy
Saˆo Jezernik PhD**ETH Z?rich, Automatic Control Laboratory; , Gery Colombo PhD‹‹Paraplegic Center ParaCare, University Hospital Balgrist; and , Thierry Keller PhD**ETH Z?rich, Automatic Control Laboratory; , Hansruedi Frueh PhD··University of Z?rich, Institute for Informatics, Artificial Intelligence Laboratory, Z?rich, Switzerland, Manfred Morari PhD*
Address correspondence and reprint requests to: Saˆo Jezernik, PhD, ETH Z?rich (Swiss Federal Institute of Technology), Automatic Control Laboratory, Physikstrasse 3, ETH Z?rich/ETL K 28, CH-8092 Z?rich, Switzerland. Email: jezernik@aut.ee.ethz.ch.
Financial support: The Swiss Commission for Technology and Innovation (Proj. Nr. 4005.1); The Swiss National Science Foundation (Proj. Nr. 3152-062025.00/1).
Key Words: central-pattern generator model, electrical stimulation, FES control, robotic rehabilitation, treadmill training.
Abstract
The aim of this article is to introduce the robotic orthosis Lokomat, developed to automate treadmill training rehabilitation of locomotion for spinal cord injured and stroke patients, to the Functional Electrical Stimulation (FES) and Neuromodulation research communities, and to report on our newly conducted research. We first illustrate the primary use of Lokomat in rehabilitation and focus on control aspects and algorithms associated with robotic rehabilitation of locomotion. Then we describe two applications where the Lokomat was used as a research tool. The first application is closed-loop control of the FES-induced shank movement and the second is the development of a neural network model of the spinal locomotor centers. This model was used to derive a neural locomotion controller for the Lokomat.
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