Evidence map›Paper›PMID 35009661›Full record

ArticleSensors (Basel, Switzerland)2021

Development and Evaluation of BenchBalance: A System for Benchmarking Balance Capabilities of Wearable Robots and Their Users.

Cristina Bayón, Gabriel Delgado-Oleas, Leticia Avellar, Francesca Bentivoglio, Francesco Di Tommaso, Nevio L Tagliamonte, Eduardo Rocon, Edwin H F van Asseldonk

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
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.

Cristina BayónDepartment of Biomechanical Engineering, University of Twente, 7522 NB Enschede, The Netherlands.ORCID 0000-0003-1825-1265
Gabriel Delgado-OleasCentro de Automática y Robótica, Universidad Politécnica de Madrid, 28500 Madrid, Spain.
Leticia AvellarCentro de Automática y Robótica, Universidad Politécnica de Madrid, 28500 Madrid, Spain.ORCID 0000-0002-1425-6395
Francesca BentivoglioUniversità Campus Bio-Medico di Roma, 00128 Rome, Italy.
Francesco Di TommasoUniversità Campus Bio-Medico di Roma, 00128 Rome, Italy.ORCID 0000-0003-0086-9075
Nevio L TagliamonteUniversità Campus Bio-Medico di Roma, 00128 Rome, Italy.
Eduardo RoconCentro de Automática y Robótica, Universidad Politécnica de Madrid, 28500 Madrid, Spain.ORCID 0000-0001-9618-2176
Edwin H F van AsseldonkDepartment of Biomechanical Engineering, University of Twente, 7522 NB Enschede, The Netherlands.ORCID 0000-0003-1534-2348

Funding

EASTERN COOPERATIVE ONCOLOGY GROUPU10CA016116 · NCI · JOHNS HOPKINS UNIVERSITY · PI FORASTIERE, ARLENE ANN · 1985 to 2013
$4.0M
NCI NIH HHS U10 CA016116
6 · The paper itself

Abstract

Recent advances in the control of overground exoskeletons are being centered on improving balance support and decreasing the reliance on crutches. However, appropriate methods to quantify the stability of these exoskeletons (and their users) are still under development. A reliable and reproducible balance assessment is critical to enrich exoskeletons' performance and their interaction with humans. In this work, we present the BenchBalance system, which is a benchmarking solution to conduct reproducible balance assessments of exoskeletons and their users. Integrating two key elements, i.e., a hand-held perturbator and a smart garment, BenchBalance is a portable and low-cost system that provides a quantitative assessment related to the reaction and capacity of wearable exoskeletons and their users to respond to controlled external perturbations. A software interface is used to guide the experimenter throughout a predefined protocol of measurable perturbations, taking into account antero-posterior and mediolateral responses. In total, the protocol is composed of sixteen perturbation conditions, which vary in magnitude and location while still controlling their orientation. The data acquired by the interface are classified and saved for a subsequent analysis based on synthetic metrics. In this paper, we present a proof of principle of the BenchBalance system with a healthy user in two scenarios: subject not wearing and subject wearing the H2 lower-limb exoskeleton. After a brief training period, the experimenter was able to provide the manual perturbations of the protocol in a consistent and reproducible way. The balance metrics defined within the BenchBalance framework were able to detect differences in performance depending on the perturbation magnitude, location, and the presence or not of the exoskeleton. The BenchBalance system will be integrated at EUROBENCH facilities to benchmark the balance capabilities of wearable exoskeletons and their users.

Indexed as

Exoskeleton DeviceWearable Electronic DevicesBenchmarkingCrutchesHumansLower Extremityassessmentbalancebenchmarkingexoskeletons

Identifiers

PMID35009661
PMCPMC8747156

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.