Evidence map›Paper›PMID 37250671›Full record

ReviewFrontiers in neurorobotics2023

Recent advancements in multimodal human-robot interaction.

Hang Su, Wen Qi, Jiahao Chen, Chenguang Yang, Juan Sandoval, Med Amine Laribi

Abstract readReview
In one paragraph

Review in Frontiers in neurorobotics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 5 pooled it
–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

23 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  13. Can humanoid robots be used as a cognitive offloading tool?Cognitive research: principles and implications · 2025
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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

6 authors.

Hang SuDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
Wen QiSchool of Future Technology, South China University of Technology, Guangzhou, China.
Jiahao ChenState Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Chenguang YangBristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom.
Juan SandovalDepartment of GMSC, Pprime Institute, CNRS, ENSMA, University of Poitiers, Poitiers, France.
Med Amine LaribiDepartment of GMSC, Pprime Institute, CNRS, ENSMA, University of Poitiers, Poitiers, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotics have advanced significantly over the years, and human-robot interaction (HRI) is now playing an important role in delivering the best user experience, cutting down on laborious tasks, and raising public acceptance of robots. New HRI approaches are necessary to promote the evolution of robots, with a more natural and flexible interaction manner clearly the most crucial. As a newly emerging approach to HRI, multimodal HRI is a method for individuals to communicate with a robot using various modalities, including voice, image, text, eye movement, and touch, as well as bio-signals like EEG and ECG. It is a broad field closely related to cognitive science, ergonomics, multimedia technology, and virtual reality, with numerous applications springing up each year. However, little research has been done to summarize the current development and future trend of HRI. To this end, this paper systematically reviews the state of the art of multimodal HRI on its applications by summing up the latest research articles relevant to this field. Moreover, the research development in terms of the input signal and the output signal is also covered in this manuscript.

Indexed as

human–robot interactionmulti-modal feedbackmulti-modal human–robot interactionmulti-modal signal processingphysical human–robot interaction

Identifiers

PMID37250671
PMCPMC10210148

What OpenQuestion holds

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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.