Evidence map›Paper›PMID 35869154›Full record

ArticleScientific reports2022

Face mediated human-robot interaction for remote medical examination.

Thilina D Lalitharatne, Leone Costi, Ryman Hashem, Ilana Nisky, Rachael E Jack, Thrishantha Nanayakkara, Fumiya Iida

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. SORI: A softness-rendering interface to unravel the nature of softness perception.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Article
  6. Metaverse Wearables for Immersive Digital Healthcare: A Review.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Review
  7. Vocal pain expression augmentation for a robopatient.Frontiers in robotics and AI · 2023
    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

7 authors.

Thilina D LalitharatneDepartment of Engineering, University of Cambridge, Cambridge, UK. t.lalitharatne@imperial.ac.uk.
Leone CostiDepartment of Engineering, University of Cambridge, Cambridge, UK.
Ryman HashemDepartment of Engineering, University of Cambridge, Cambridge, UK.
Ilana NiskyDepartment of Engineering, University of Cambridge, Cambridge, UK.
Rachael E JackSchool of Psychology and Neuroscience, University of Glasgow, Glasgow, UK.
Thrishantha NanayakkaraDyson School of Design Engineering, Imperial College London, London, UK.
Fumiya IidaDepartment of Engineering, University of Cambridge, Cambridge, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Realtime visual feedback from consequences of actions is useful for future safety-critical human-robot interaction applications such as remote physical examination of patients. Given multiple formats to present visual feedback, using face as feedback for mediating human-robot interaction in remote examination remains understudied. Here we describe a face mediated human-robot interaction approach for remote palpation. It builds upon a robodoctor-robopatient platform where user can palpate on the robopatient to remotely control the robodoctor to diagnose a patient. A tactile sensor array mounted on the end effector of the robodoctor measures the haptic response of the patient under diagnosis and transfers it to the robopatient to render pain facial expressions in response to palpation forces. We compare this approach against a direct presentation of tactile sensor data in a visual tactile map. As feedback, the former has the advantage of recruiting advanced human capabilities to decode expressions on a human face whereas the later has the advantage of being able to present details such as intensity and spatial information of palpation. In a user study, we compare these two approaches in a teleoperated palpation task to find the hard nodule embedded in the remote abdominal phantom. We show that the face mediated human-robot interaction approach leads to statistically significant improvements in localizing the hard nodule without compromising the nodule position estimation time. We highlight the inherent power of facial expressions as communicative signals to enhance the utility and effectiveness of human-robot interaction in remote medical examinations.

Indexed as

RoboticsFeedbackFeedback, SensoryHumansPalpationTouch

Identifiers

PMID35869154
PMCPMC9307637

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.