Evidence map›Paper›PMID 41781418›Full record

ArticleScientific reports2026

Haptic feedback in violin education as a case study of robotic exoskeleton-mediated motor learning.

Adriaan Campo, Emanuele Peperoni, Stefano Laszlo Capitani, Roberto Conti, Simona Crea, Nicola Di Stefano, Francesco Di Tommaso, Francesco Giovacchini, Canan Gener, Lorenzo Grazi and 9 more

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Adriaan CampoFaculty of Arts and Philosophy, Institute of Psychoacoustics and Electronic Music (IPEM), Ghent University, Ghent, Belgium. adriaan.campo@ugent.be.
Emanuele PeperoniThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Stefano Laszlo CapitaniThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Roberto ContiIUVO S.r.l, Pontedera, Pisa, Italy.
Simona CreaThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Nicola Di StefanoInstitute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Rome, Italy.
Francesco Di TommasoUniversità Campus Bio-Medico di Roma, Rome, Italy.
Francesco GiovacchiniIUVO S.r.l, Pontedera, Pisa, Italy.
Canan GenerFaculty of Arts and Philosophy, Institute of Psychoacoustics and Electronic Music (IPEM), Ghent University, Ghent, Belgium.
Lorenzo GraziThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Luca MorelliIUVO S.r.l, Pontedera, Pisa, Italy.
Alessia NoccaroNeurorobotics Lab, Newcastle University, Newcastle upon Tyne, UK.
Andrea ParriIUVO S.r.l, Pontedera, Pisa, Italy.
Nevio Luigi TagliamonteUniversità Campus Bio-Medico di Roma, Rome, Italy.
Emilio TrigiliThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Nicola VitielloThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Shalan AlhamwyDe Centrale, Ghent, Belgium.
Domenico FormicaNeurorobotics Lab, Newcastle University, Newcastle upon Tyne, UK.
Marc LemanFaculty of Arts and Philosophy, Institute of Psychoacoustics and Electronic Music (IPEM), Ghent University, Ghent, Belgium.

Funding

H2020/ICT 871803
6 · The paper itself

Abstract

This study explores the use of an upper-limb wearable exoskeleton for teaching violin technique to novices through haptic-assisted training. The educational potential of this technology was evaluated using a framework that integrated quantitative kinematic metrics and qualitative assessments, comparing a group receiving haptic feedback (N = 12) with a control group that did not (N = 12) in a mixed between-within-subjects design. Results from a double-blind expert panel indicated that participants trained with the exoskeleton outperformed the control group during recall measurements. In addition, spatial and spatiotemporal - but not temporal - kinematic metrics related to bowing technique improved significantly during training, with gains persisting during recall, and these outcomes were supported by self-reported user assessments. However, subtle features of the technology also became apparent, including interference with natural shoulder movements, exposing areas for refinement. In conclusion, this study suggests that haptic-assisted training with an exoskeleton can enhance specific motor skills in violin playing, highlighting promising directions for future research in educational technology and providing a quantitative framework for assessing motor skill development in haptic-assisted learning, which can further support the development and validation of educational technologies. However, given the absence of long-term retention measurements and the limited generalizability associated with the small sample size, the findings of this pilot study should be interpreted with caution.

Indexed as

Exoskeleton DeviceFeedback, SensoryLearningMotor SkillsMusicRoboticsAdultBiomechanical PhenomenaDouble-Blind MethodFemaleHumansMaleYoung Adult

Identifiers

PMID41781418
PMCPMC13125633

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.