Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 256

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Gait rehabilitation machines based on programmable footplates

Open access
Schmidt, Henning, Werner, Cordula, Bernhardt, Rolf, Hesse, Stefan, Krüger, Jörg·2007·Journal of NeuroEngineering and Rehabilitation

Abstract

BACKGROUND: Gait restoration is an integral part of rehabilitation of brain lesioned patients. Modern concepts favour a task-specific repetitive approach, i.e. who wants to regain walking has to walk, while tone-inhibiting and gait preparatory manoeuvres had dominated therapy before. Following the first mobilization out of the bed, the wheelchair-bound patient should have the possibility to practise complex gait cycles as soon as possible. Steps in this direction were treadmill training with partial body weight support and most recently gait machines enabling the repetitive training of even surface gait and even of stair climbing. RESULTS: With treadmill training harness-secured and partially relieved wheelchair-mobilised patients could practise up to 1000 steps per session for the first time. Controlled trials in stroke and SCI patients, however, failed to show a superior result when compared to walking exercise on the floor. Most likely explanation was the effort for the therapists, e.g. manually setting the paretic limbs during the swing phase resulting in a too little gait intensity. The next steps were gait machines, either consisting of a powered exoskeleton and a treadmill (Lokomat, AutoAmbulator) or an electromechanical solution with the harness secured patient placed on movable foot plates (Gait Trainer GT I). For the latter, a large multi-centre trial with 155 non-ambulatory stroke patients (DEGAS) revealed a superior gait ability and competence in basic activities of living in the experimental group. The HapticWalker continued the end effector concept of movable foot plates, now fully programmable and equipped with 6 DOF force sensors. This device for the first time enables training of arbitrary walking situations, hence not only the simulation of floor walking but also for example of stair climbing and perturbations. CONCLUSION: Locomotor therapy is a fascinating new tool in rehabilitation, which is in line with modern principles of motor relearning promoting a task-specific repetitive approach. Sophisticated technical developments and positive randomized controlled trials form the basis of a growing acceptance worldwide to the benefits or our patients.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/1743-0003-4-2

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 34 references

Cited by

See all 256

Metadata

Authors
Schmidt, H., Werner, C., Bernhardt, R., Hesse, S., & Krüger, J.
Venue
Journal of NeuroEngineering and Rehabilitation
Published
2007-02-09
Volume
4
Issue
1
Pages
2-2
ISSN
1743-0003 (ISSN-L)
OpenAlex
W2150151850
Cited by
256
References
34
FWCI
10.50
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Gait rehabilitation machines based on programmable footplates. https://app.cochat.ai/papers/10.1186/1743-0003-4-2
The paper
Schmidt, H., Werner, C., Bernhardt, R., Hesse, S., & Krüger, J. (2007). Gait rehabilitation machines based on programmable footplates. Journal of NeuroEngineering and Rehabilitation. https://doi.org/10.1186/1743-0003-4-2

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.