Evidence map›Paper›PMID 42481576›Full record

ArticleScientific reports2026

Intuitive therapist robot patient physical interaction is worth a thousand words.

Beatrice Luciani, Alex van den Berg, Matti Lang, Alexandre L Ratschat, Laura Marchal-Crespo

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

5 authors.

Beatrice LucianiDepartment of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands. bluciani@tudelft.nl.ORCID https://orcid.org/0000-0002-6611-4655
Alex van den BergDepartment of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands.
Matti LangDepartment of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands.
Alexandre L RatschatDepartment of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands.
Laura Marchal-CrespoDepartment of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands.

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek NWO, VIDI Grant Nr. 18934
6 · The paper itself

Abstract

Robotic systems can enhance the amount and repeatability of physical guided motor training. Yet their real-world adoption is limited, partly due to non-intuitive trainer/therapist-trainee/patient interactions. To address this gap, we present a haptic teleoperation system for trainers to remotely guide and monitor the movements of a trainee wearing an arm exoskeleton. The trainer can physically interact with the exoskeleton through a commercial handheld haptic device via virtual contact points at the exoskeleton's elbow and wrist, allowing intuitive guidance. Thirty-two participants tested the system in a trainer-trainee paradigm, comparing our haptic demonstration system with conventional visual demonstration in guiding trainees in executing arm poses. Quantitative analyses showed that haptic demonstration significantly reduced movement completion time and improved smoothness, while speech analysis-using large language models for automated transcription and categorization of verbal commands-revealed fewer verbal instructions. The haptic demonstration did not result in higher reported mental and physical effort by trainers compared to the visual demonstration, while trainers reported greater competence and trainees lower physical demand. These findings support the feasibility of our proposed interface for effective remote human-robot physical interaction. Future work should assess its usability and efficacy for clinical populations in restoring clinicians' sense of agency during robot-assisted therapy.

Identifiers

PMID42481576
PMCPMC13683037

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.