Evidence map›Paper›PMID 32843058›Full record

ArticleJournal of neuroengineering and rehabilitation2020

Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand.

Cristina Piazza, Ann M Simon, Kristi L Turner, Laura A Miller, Manuel G Catalano, Antonio Bicchi, Levi J Hargrove

Open access · goldAbstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-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

3 citing papers in PubMed, 21 citations in OpenAlex.

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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

7 authors at 4 institutions in 3 countries.

Cristina PiazzaDepartment of Physical Medicine and Rehabilitation, Northwestern University, Chicago, 60611, IL, USA. cristina.piazza@northwestern.edu.ORCID 0000-0002-0358-8677
Ann M SimonDepartment of Physical Medicine and Rehabilitation, Northwestern University, Chicago, 60611, IL, USA.
Kristi L TurnerThe Regenstein Foundation Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, 60611, IL, USA.
Laura A MillerDepartment of Physical Medicine and Rehabilitation, Northwestern University, Chicago, 60611, IL, USA.
Manuel G CatalanoIstituto Italiano di Tecnologia, Genoa, 16163, Italy.
Antonio BicchiIstituto Italiano di Tecnologia, Genoa, 16163, Italy.
Levi J HargroveDepartment of Physical Medicine and Rehabilitation, Northwestern University, Chicago, 60611, IL, USA.
Northwestern University · USItalian Institute of Technology · ITPiaggio (Italy) · ITShirley Ryan AbilityLab · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundState-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently, the translation of neuroscientific theories (i.e. postural synergies) in software and hardware architecture of artificial devices is opening new approaches for the design and control of upper-limb prostheses.

methodsFollowing these emerging principles, previous research on the SoftHand Pro, which embeds one physical synergy, showed promising results in terms of intuitiveness, robustness, and grasping performance. To explore these principles also in hands with augmented capabilities, this paper describes the SoftHand 2 Pro, a second generation of the device with 19 degrees-of-freedom and a second synergistic layer. After a description of the proposed device, the work explores a continuous switching control method based on a myoelectric pattern recognition classifier.

resultsThe combined system was validated using standardized assessments with able-bodied and, for the first time, amputee subjects. Results show an average improvement of more than 30% of fine grasp capabilities and about 10% of hand function compared with the first generation SoftHand Pro.

conclusionsEncouraging results suggest how this approach could be a viable way towards the design of more natural, reliable, and intuitive dexterous hands.

Indexed as

Artificial LimbsHandAdultAmputeesElectromyographyFemaleHand StrengthHealthy VolunteersHumansMaleProsthesis DesignRoboticsSoftwareYoung AdultAdaptive synergiesBionic handMyoelectric controlSoft robotics

Identifiers

PMID32843058
PMCPMC7447577
OpenAlexW3080109406

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.