Evidence map›Paper›PMID 33339874›Full record

ArticleScientific reports2020

Analogous adaptations in speed, impulse and endpoint stiffness when learning a real and virtual insertion task with haptic feedback.

Atsushi Takagi, Giovanni De Magistris, Geyun Xiong, Alain Micaelli, Hiroyuki Kambara, Yasuharu Koike, Jonathan Savin, Jacques Marsot, Etienne Burdet

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. 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
0.3field-weighted citation impact, top 42% 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, 4 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

9 authors at 5 institutions in 3 countries.

Atsushi TakagiNTT Communication Science Laboratories, 3-1 Morinosato Wakamiya, Atsugi, Kanagawa, 243-0198, Japan. atsushi.takagi.yx@hco.ntt.co.jp.
Giovanni De MagistrisCEA, LIST, LSI, Rue de Noetzlin, 91190, Gif-sur-Yvette, France.
Geyun XiongTokyo Institute of Technology, 4259 Nagatsuta-cho, Yokohama, 226-8503, Japan.
Alain MicaelliCEA, LIST, LSI, Rue de Noetzlin, 91190, Gif-sur-Yvette, France.
Hiroyuki KambaraTokyo Institute of Technology, 4259 Nagatsuta-cho, Yokohama, 226-8503, Japan.
Yasuharu KoikeTokyo Institute of Technology, 4259 Nagatsuta-cho, Yokohama, 226-8503, Japan.
Jonathan SavinInstitut National de Recherche Et de Sécurité (INRS), Rue du Morvan, CS 60027, 54519, Vandoeuvre-lès-Nancy, France.
Jacques MarsotInstitut National de Recherche Et de Sécurité (INRS), Rue du Morvan, CS 60027, 54519, Vandoeuvre-lès-Nancy, France.
Etienne BurdetImperial College of Science, Technology and Medicine, South Kensington, London, SW7 2AZ, UK.
Tokyo Institute of Technology · JPInstitut National de Recherche et de Sécurité · FRCommissariat à l'Énergie Atomique et aux Énergies Alternatives · FRImperial College London · GBLaboratoire d'Intégration des Systèmes et des Technologies · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans have the ability to use a diverse range of handheld tools. Owing to its versatility, a virtual environment with haptic feedback of the force is ideally suited to investigating motor learning during tool use. However, few simulators exist to recreate the dynamic interactions during real tool use, and no study has compared the correlates of motor learning between a real and virtual tooling task. To this end, we compared two groups of participants who either learned to insert a real or virtual tool into a fixture. The trial duration, the movement speed, the force impulse after insertion and the endpoint stiffness magnitude decreased as a function of trials, but they changed at comparable rates in both environments. A ballistic insertion strategy observed in both environments suggests some interdependence when controlling motion and controlling interaction, contradicting a prominent theory of these two control modalities being independent of one another. Our results suggest that the brain learns real and virtual insertion in a comparable manner, thereby supporting the use of a virtual tooling task with haptic feedback to investigate motor learning during tool use.

Indexed as

Adaptation, PhysiologicalAdultBrainComputer SimulationFeedbackHumansLaparoscopyLearningMaleMotor ActivityNeurosciencesPsychomotor PerformanceTouchUser-Computer InterfaceYoung Adult

Identifiers

PMID33339874
PMCPMC7749137
OpenAlexW3114516090

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.