Evidence map›Paper›PMID 42798744›Full record

SynthesisFrontiers in robotics and AI2026

Emotion recognition and human-robot interaction: a systematic review of methods and applications.

Iraide Seijo Barquin, Juan Alejandro Castano, Virginia Ruiz Garate, Antonio J Del-Ama

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Frontiers in robotics and AI, 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

4 authors.

Iraide Seijo BarquinRobotics and Automation Department, Faculty of Engineering, Mondragon Unibertsitatea, Bilbao, Spain.
Juan Alejandro CastanoApplied Mathematics, Materials Science and Electronic Technology Department, Bioengineering Systems and Technologies Research Group (BeST), Rey Juan Carlos University, Móstoles, Spain.
Virginia Ruiz GarateRobotics and Automation Department, Faculty of Engineering, Mondragon Unibertsitatea, Bilbao, Spain.
Antonio J Del-AmaApplied Mathematics, Materials Science and Electronic Technology Department, Bioengineering Systems and Technologies Research Group (BeST), Rey Juan Carlos University, Móstoles, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Physical human-robot interaction involves a tightly coupled cognitive interaction with the user. The emotional state of the user is therefore a key factor influencing engagement, motivation, and long-term acceptance. This review explores recent developments in emotion-aware technologies, particularly facial expression recognition and multimodal affect detection, and their potential to make assistive robots more adaptive and human-centred. By analysing current methodologies, emerging trends, and ethical considerations, we show how the integration of emotional intelligence can transform robotic assistance, shifting from reactive mechanisms to genuinely empathetic, socio-psychological, and context-aware assistive partners.

Indexed as

affective computingassistive roboticsemotionfacial recognitionmultimodal interaction

Identifiers

PMID42798744
PMCPMC13612989

What OpenQuestion holds

Textmetadata
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.