Evidence map›Paper›PMID 34179107›Full record

ArticleFrontiers in robotics and AI2021

Integration of a Passive Exoskeleton and a Robotic Supernumerary Finger for Grasping Compensation in Chronic Stroke Patients: The SoftPro Wearable System.

Gionata Salvietti, Leonardo Franco, Martin Tschiersky, Gerjan Wolterink, Matteo Bianchi, Antonio Bicchi, Federica Barontini, Manuel Catalano, Giorgio Grioli, Mattia Poggiani and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in robotics and AI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 26% of its field
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

1 citing paper in PubMed, 12 citations in OpenAlex.

  1. 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

12 authors at 4 institutions in 2 countries.

Gionata SalviettiSiena Robotics and Systems Laboratory Group, Department of Information Engineering and Mathematical Science, University of Siena, Siena, Italy.
Leonardo FrancoSiena Robotics and Systems Laboratory Group, Department of Information Engineering and Mathematical Science, University of Siena, Siena, Italy.
Martin TschierskyChair of Precision Engineering, Department of Engineering Technology, University of Twente, Enschede, Netherlands.
Gerjan WolterinkBiomedical Signals and Systems (BSS) and Robotics and Mechatronics (RAM) Group, Department of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, Netherlands.
Matteo BianchiResearch Centre "E. Piaggio" and Department of Information Engineering, University of Pisa, Pisa, Italy.
Antonio BicchiSoft Robotics for Human Cooperation and Rehabilitation, Istituto Italiano di Tecnologia, Genova, Italy.
Federica BarontiniSoft Robotics for Human Cooperation and Rehabilitation, Istituto Italiano di Tecnologia, Genova, Italy.
Manuel CatalanoSoft Robotics for Human Cooperation and Rehabilitation, Istituto Italiano di Tecnologia, Genova, Italy.
Giorgio GrioliSoft Robotics for Human Cooperation and Rehabilitation, Istituto Italiano di Tecnologia, Genova, Italy.
Mattia PoggianiSoft Robotics for Human Cooperation and Rehabilitation, Istituto Italiano di Tecnologia, Genova, Italy.
Simone RossiBrain Investigation and Neuromodulation Lab, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
Domenico PrattichizzoSiena Robotics and Systems Laboratory Group, Department of Information Engineering and Mathematical Science, University of Siena, Siena, Italy.
Italian Institute of Technology · ITUniversity of Siena · ITUniversity of Twente · NLUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Upper-limb impairments are all-pervasive in Activities of Daily Living (ADLs). As a consequence, people affected by a loss of arm function must endure severe limitations. To compensate for the lack of a functional arm and hand, we developed a wearable system that combines different assistive technologies including sensing, haptics, orthotics and robotics. The result is a device that helps lifting the forearm by means of a passive exoskeleton and improves the grasping ability of the impaired hand by employing a wearable robotic supernumerary finger. A pilot study involving 3 patients, which was conducted to test the capability of the device to assist in performing ADLs, confirmed its usefulness and serves as a first step in the investigation of novel paradigms for robotic assistance.

Indexed as

assistive roboticsexoskeletonshuman-robot interfacesupper-limb impairmentswearable robotics

Identifiers

PMID34179107
PMCPMC8222583
OpenAlexW3171111633

What OpenQuestion holds

Textmetadata
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.