Evidence map›Paper›PMID 36875662›Full record

ArticleFrontiers in neuroscience2023

Object stiffness recognition and vibratory feedback without

Giulia Bruni, Andrea Marinelli, Anna Bucchieri, Nicolò Boccardo, Giulia Caserta, Dario Di Domenico, Giacinto Barresi, Astrid Florio, Michele Canepa, Federico Tessari and 2 more

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2023. 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
–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

1 citing paper in PubMed.

  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.

Giulia BruniRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Andrea MarinelliRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Anna BucchieriRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Nicolò BoccardoRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Giulia CasertaRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Dario Di DomenicoRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Giacinto BarresiRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Astrid FlorioRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Michele CanepaRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Federico TessariNewman Laboratory, Massachusetts Institute of Technology, Boston, MA, United States.
Matteo LaffranchiRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.
Lorenzo De MichieliRehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In recent years, hand prostheses achieved relevant improvements in term of both motor and functional recovery. However, the rate of devices abandonment, also due to their poor embodiment, is still high. The embodiment defines the integration of an external object - in this case a prosthetic device - into the body scheme of an individual. One of the limiting factors causing lack of embodiment is the absence of a direct interaction between user and environment. Many studies focused on the extraction of tactile information Methods: Based on these initial findings, this work presents the design, implementation and clinical validation of a novel real-time stiffness detection strategy, without Results: The classifier achieved excellent performance in terms of F1Score (94.93%). Further, the able-bodied subjects and amputees were able to successfully detect the objects' stiffness with a F1Score of 94.08% and 86.41%, respectively, by using our proposed feedback strategy. This strategy allowed amputees to quickly recognize the objects' stiffness (response time of 2.82 s), indicating high intuitiveness, and it was overall appreciated as demonstrated by the questionnaire. Furthermore, an embodiment improvement was also obtained as highlighted by the proprioceptive drift toward the prosthesis (0.7 cm).

Indexed as

closed-loop controlHannes prosthetic handnon-linear logistic regressionstiffness recognitionvibromotorvibrotactile feedback

Identifiers

PMID36875662
PMCPMC9978002

What OpenQuestion holds

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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.