Evidence map›Paper›PMID 28806995›Full record

ReviewJournal of neuroengineering and rehabilitation2017

Robot-supported assessment of balance in standing and walking.

Camila Shirota, Edwin van Asseldonk, Zlatko Matjačić, Heike Vallery, Pierre Barralon, Serena Maggioni, Jaap H Buurke, Jan F Veneman

Abstract readReview
In one paragraph

Review in Journal of neuroengineering and rehabilitation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Review
  9. Promoting Functional and Independent Sitting in Children With Cerebral Palsy Using the Robotic Trunk Support Trainer.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Camila ShirotaRehabilitation Engineering Lab, Institute of Robotics and Intelligent Systems, Department of Health Sciences and Technology, ETH Zürich, Lengghalde 5, 8092, Zürich, Switzerland.
Edwin van AsseldonkDepartment of Biomechanical Engineering, MIRA, University of Twente, Drienerlolaan 5, 7522 NB, Enschede, The Netherlands.
Zlatko MatjačićUniversity Rehabilitation Institute, Republic of Slovenia, Linhartova 51, SI-1000, Ljubljana, Slovenia.
Heike ValleryFaculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands.
Pierre BarralonHealth Division, Tecnalia Research and Innovation, Paseo Mikeletegi 1, 20009, Donostia-San Sebastian, Spain.
Serena MaggioniSensory-Motor Systems Lab, Institute of Robotics and Intelligent Systems, Department of Health Sciences and Technology, ETH Zürich, Sonneggstrasse 3, 8092, Zürich, Switzerland.
Jaap H BuurkeRoessingh Research and Development, Roessinghsbleekweg 33b, 7522 AH, Enschede, The Netherlands.
Jan F VenemanHealth Division, Tecnalia Research and Innovation, Paseo Mikeletegi 1, 20009, Donostia-San Sebastian, Spain. jan.veneman@tecnalia.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinically useful and efficient assessment of balance during standing and walking is especially challenging in patients with neurological disorders. However, rehabilitation robots could facilitate assessment procedures and improve their clinical value. We present a short overview of balance assessment in clinical practice and in posturography. Based on this overview, we evaluate the potential use of robotic tools for such assessment. The novelty and assumed main benefits of using robots for assessment are their ability to assess 'severely affected' patients by providing assistance-as-needed, as well as to provide consistent perturbations during standing and walking while measuring the patient's reactions. We provide a classification of robotic devices on three aspects relevant to their potential application for balance assessment: 1) how the device interacts with the body, 2) in what sense the device is mobile, and 3) on what surface the person stands or walks when using the device. As examples, nine types of robotic devices are described, classified and evaluated for their suitability for balance assessment. Two example cases of robotic assessments based on perturbations during walking are presented. We conclude that robotic devices are promising and can become useful and relevant tools for assessment of balance in patients with neurological disorders, both in research and in clinical use. Robotic assessment holds the promise to provide increasingly detailed assessment that allows to individually tailor rehabilitation training, which may eventually improve training effectiveness.

Indexed as

Postural BalanceWalkingHumansMaleNervous System DiseasesPhysical Therapy ModalitiesRoboticsAssessmentBalance performancePosturographyRehabilitation robotsStandingWalking

Identifiers

PMID28806995
PMCPMC5556664

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.