Evidence map›Paper›PMID 39135110›Full record

ArticleJournal of neuroengineering and rehabilitation2024

A compact solution for vibrotactile proprioceptive feedback of wrist rotation and hand aperture.

Andrea Marinelli, Nicolò Boccardo, Michele Canepa, Dario Di Domenico, Emanuele Gruppioni, Matteo Laffranchi, Lorenzo De Michieli, Michela Chiappalone, Marianna Semprini, Strahinja Dosen

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2024. 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
–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

3 citing papers in PubMed.

  1. Article
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  3. 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

10 authors.

Andrea MarinelliRehabTechnology Lab, Italian Institute of Technology, Via Morego, 30, Genova, GE, 16163, Italy. andrea.marinelli@iit.it.
Nicolò BoccardoRehabTechnology Lab, Italian Institute of Technology, Via Morego, 30, Genova, GE, 16163, Italy.
Michele CanepaRehabTechnology Lab, Italian Institute of Technology, Via Morego, 30, Genova, GE, 16163, Italy.
Dario Di DomenicoRehabTechnology Lab, Italian Institute of Technology, Via Morego, 30, Genova, GE, 16163, Italy.
Emanuele GruppioniCentro Protesi INAIL, Istituto Nazionale per l'Assicurazione contro gli Infortuni sul Lavoro, Vigorso di Budrio, Italy.
Matteo LaffranchiRehabTechnology Lab, Italian Institute of Technology, Via Morego, 30, Genova, GE, 16163, Italy.
Lorenzo De MichieliRehabTechnology Lab, Italian Institute of Technology, Via Morego, 30, Genova, GE, 16163, Italy.
Michela ChiappaloneRehabTechnology Lab, Italian Institute of Technology, Via Morego, 30, Genova, GE, 16163, Italy.
Marianna SempriniRehabTechnology Lab, Italian Institute of Technology, Via Morego, 30, Genova, GE, 16163, Italy.
Strahinja DosenNeurorehabilitation Systems, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark. sdosen@hst.aau.dk.

Funding

Istituto Nazionale Assicurazione Infortuni sul Lavoro Dexter Hand (PR23-PAS-P1)Istituto Nazionale Assicurazione Infortuni sul Lavoro iHannes (PR19-PAS-P1)
6 · The paper itself

Abstract

backgroundClosing the control loop between users and their prostheses by providing artificial sensory feedback is a fundamental step toward the full restoration of lost sensory-motor functions.

methodsWe propose a novel approach to provide artificial proprioceptive feedback about two degrees of freedom using a single array of 8 vibration motors (compact solution). The performance afforded by the novel method during an online closed-loop control task was compared to that achieved using the conventional approach, in which the same information was conveyed using two arrays of 8 and 4 vibromotors (one array per degree of freedom), respectively. The new method employed Gaussian interpolation to modulate the intensity profile across a single array of vibration motors (compact feedback) to convey wrist rotation and hand aperture by adjusting the mean and standard deviation of the Gaussian, respectively. Ten able-bodied participants and four transradial amputees performed a target achievement control test by utilizing pattern recognition with compact and conventional vibrotactile feedback to control the Hannes prosthetic hand (test conditions). A second group of ten able-bodied participants performed the same experiment in control conditions with visual and auditory feedback as well as no-feedback.

resultsConventional and compact approaches resulted in similar positioning accuracy, time and path efficiency, and total trial time. The comparison with control condition revealed that vibrational feedback was intuitive and useful, but also underlined the power of incidental feedback sources. Notably, amputee participants achieved similar performance to that of able-bodied participants.

conclusionsThe study therefore shows that the novel feedback strategy conveys useful information about prosthesis movements while reducing the number of motors without compromising performance. This is an important step toward the full integration of such an interface into a prosthesis socket for clinical use.

Indexed as

Artificial LimbsFeedback, SensoryHandProprioceptionVibrationWristAdultAmputeesFemaleHumansMaleMiddle AgedRotationTouchYoung AdultClosed-loop controlGaussian interpolationHannes handMultichannel stimulationProprioceptive feedbackSpatial encodingVibromotors

Identifiers

PMID39135110
PMCPMC11320866

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.