Evidence map›Paper›PMID 36991743›Full record

SynthesisSensors (Basel, Switzerland)2023

Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review.

Tobias Moeller, Felix Moehler, Janina Krell-Roesch, Miha Dežman, Charlotte Marquardt, Tamim Asfour, Thorsten Stein, Alexander Woll

Abstract readSystematic Review
In one paragraph

Synthesis in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
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.

Tobias MoellerInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.ORCID 0000-0003-0454-4833
Felix MoehlerInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.
Janina Krell-RoeschInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.
Miha DežmanInstitute for Anthropomatics and Robotics, High Performance Humanoid Technologies (H2T), Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.ORCID 0000-0001-7160-749X
Charlotte MarquardtInstitute for Anthropomatics and Robotics, High Performance Humanoid Technologies (H2T), Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.ORCID 0000-0002-5757-1512
Tamim AsfourInstitute for Anthropomatics and Robotics, High Performance Humanoid Technologies (H2T), Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.ORCID 0000-0003-4879-7680
Thorsten SteinInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.ORCID 0000-0002-7885-7085
Alexander WollInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.ORCID 0000-0002-5736-2980

Funding

Carl Zeiss Foundation JuBot
6 · The paper itself

Abstract

Exoskeletons are a promising tool to support individuals with a decreased level of motor performance. Due to their built-in sensors, exoskeletons offer the possibility of continuously recording and assessing user data, for example, related to motor performance. The aim of this article is to provide an overview of studies that rely on using exoskeletons to measure motor performance. Therefore, we conducted a systematic literature review, following the PRISMA Statement guidelines. A total of 49 studies using lower limb exoskeletons for the assessment of human motor performance were included. Of these, 19 studies were validity studies, and six were reliability studies. We found 33 different exoskeletons; seven can be considered stationary, and 26 were mobile exoskeletons. The majority of the studies measured parameters such as range of motion, muscle strength, gait parameters, spasticity, and proprioception. We conclude that exoskeletons can be used to measure a wide range of motor performance parameters through built-in sensors, and seem to be more objective and specific than manual test procedures. However, since these parameters are usually estimated from built-in sensor data, the quality and specificity of an exoskeleton to assess certain motor performance parameters must be examined before an exoskeleton can be used, for example, in a research or clinical setting.

Indexed as

Exoskeleton DeviceGait Disorders, NeurologicGaitHumansLower ExtremityReproducibility of Resultsdiagnosisgaitproprioceptionrange of motionstiffnessstrengthtestwearable deviceswearable robotics

Identifiers

PMID36991743
PMCPMC10057915

What OpenQuestion holds

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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.