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Project description:
Treadmill training has been recently proposed as a new rehabilitation exercise for the spinal cord injured
patients and possibly also for the stroke patients (individuals with hemiparesis). During the treadmill
training, a periodic excitation of the cutaneous and muscular receptors provides a periodic afferent
input to the neural circuits located in the spinal cord (central pattern generator). These circuits
are responsible for coordinated muscle activation in the limbs required to generate locomotion. It was
demonstrated that the treadmill training improves the muscle activation pattern generated by the
central pattern generator (CPG), and therefore enables the patients a faster and better re-learning
of the locomotion (walking).
Especially in the beginning of the rehabilitation, patients are not able to maintain their equilibrium
and to walk by themselves. Their body is therefore supported in a harness, and their legs are moved by
physiotherapists. Because the leg movement task is very strenuous for the physiotherapists, an artificial
robotic orthosis driven by DC electric motors was built to artificially move the legs of the patients during
the treadmill training. The motors do not generate the joint torques directly, but act on the segments of the
orthosis via forces transmitted by ball screws. The gait pattern is generated by tracking the 4 reference
angle trajectories recorded in another experiment, where a healthy subject was walking in the orthosis.
In a later stage of rehabilitation when the patients are already able to produce the leg movements by
themselves, it might be advantageous to adapt the treadmill training gait pattern. The patients would
then be able to do the training more actively, which would result in active, time-coordinated muscle
contractions induced during walking. These muscle contractions would provide an additional afferent
tuning information to the CPG, and could further increase the therapeutic effect of the training.
The aim of this project is to implement and incorporate an algorithm for gait-pattern adaptation
into the robotic orthosis control scheme.
The major necessary development steps are:
1. Implementation of the force/torque measurement systems.
2. Analysis and processing of the force/torque data leading to the detection of spasms and to the detection of user’s efforts to change the gait pattern.
3. Incorporation of the force/torque measurement information into the adaptation/control scheme
(development of on-line gait-pattern adaptation algorithms).
Current/past research work includes/included: mounting and testing of the 1- and 3-axial force transducers onto Lokomat,
dynamical modeling of the Lokomat, implementation of the impedance control as well as the computed torque (feedback linearization) control schemes, biologically based neural network (NN) control of Lokomat, and development of the gait-pattern
adaptation algorithms.
So far three variants of the gait-pattern adaptation algorith have been developed:
(1) indirect joint-angle adaptation (via minimization of a torque functional), (2) direct joint-angle adaptation (via minimization of an angular acceleration functional), and (3) direct joint-angle adaptation (based on impedance control). We have also already started performing the first real-time gait-pattern adaptation experiments on healthy as well as spinal cord injured individualls.
This project is supported by the Swiss Commission for Technology and Innovation CTI (CTI Project number: 4005.1).
Collaborating companies/institutions: Hocoma Gmbh, University Clinic Balgrist (ParaCare).
