Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

188
Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role...
188
Stereotype Content Model02:16

Stereotype Content Model

14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K
Nonconscious Mimicry01:13

Nonconscious Mimicry

4.6K
Nonconscious mimicry occurs when individuals alter their mannerisms to match the behaviors and expressions of those nearby, without intention.
4.6K
Muscles for Facial Expressions01:14

Muscles for Facial Expressions

2.2K
The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
2.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same authorSame journal

Toward a Compositional Theory of Trust in Embodied Intelligence: A QNLP Framework for Modeling Context, Interaction, and Trustworthiness.

Biomimetics (Basel, Switzerland)·2026
Same author

Proprioception and vision relationship in aimed movement with restricted and reversed vision.

Applied ergonomics·2025
Same author

When Trustworthiness Meets Face: Facial Design for Social Robots.

Sensors (Basel, Switzerland)·2024
Same author

The Influence of Anthropomorphic Cues on Patients' Perceived Anthropomorphism, Social Presence, Trust Building, and Acceptance of Health Care Conversational Agents: Within-Subject Web-Based Experiment.

Journal of medical Internet research·2023
Same author

3D human ear modelling with parameterization technique and variation analysis.

Ergonomics·2023
Same author

Determinants of self-efficacy of driving behavior among young adults in the UAE: Impact of gender, culture, and varying environmental conditions in a simulated environment.

Heliyon·2023

Related Experiment Video

Updated: Jul 18, 2025

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

13.3K

Facial Anthropomorphic Trustworthiness Scale for Social Robots: A Hybrid Approach.

Yao Song1,2,3, Ameersing Luximon4, Yan Luximon3

  • 1Digital Convergence Laboratory of Chinese Cultural Inheritance and Global Communication, Sichuan University, Chengdu 610065, China.

Biomimetics (Basel, Switzerland)
|August 25, 2023
PubMed
Summary

Researchers developed a new scale, the Facial Anthropomorphic Trustworthiness towards Social Robots (FATSR-17), to measure how trustworthy a robot's face appears. This tool helps design more trustworthy social robots.

Keywords:
artificial intelligencefacescalesocial robot

More Related Videos

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.4K
One Dimensional Turing-Like Handshake Test for Motor Intelligence
14:05

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Published on: December 15, 2010

26.9K

Related Experiment Videos

Last Updated: Jul 18, 2025

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

13.3K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.4K
One Dimensional Turing-Like Handshake Test for Motor Intelligence
14:05

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Published on: December 15, 2010

26.9K

Area of Science:

  • Human-Robot Interaction
  • Robotics
  • Psychology

Background:

  • Social robots are increasingly integrated into human environments.
  • Measuring user trust in robot appearance, especially during initial encounters, is crucial but under-researched.
  • Anthropomorphism in robots significantly influences user perception and acceptance.

Purpose of the Study:

  • To develop and validate a reliable measurement scale for facial trustworthiness in anthropomorphic social robots.
  • To address the gap in quantifying user perceptions of robot facial trustworthiness.
  • To provide a tool for robot designers to enhance user trust.

Main Methods:

  • A hybrid deep convolution approach combining crowdsourcing for data collection.
  • Deep convolution and factor analysis for data processing and scale development.
  • Iterative examination and refinement to ensure psychometric properties of the scale.

Main Results:

  • Development of the Facial Anthropomorphic Trustworthiness towards Social Robots (FATSR-17) scale.
  • The FATSR-17 scale comprises 17 items across four dimensions: ethics concern, capability, positive affect, and anthropomorphism.
  • The scale demonstrated reliability and validity through rigorous testing.

Conclusions:

  • The FATSR-17 scale offers a structured toolkit for assessing robot facial trustworthiness.
  • This research facilitates the design of social robots that elicit greater user trust.
  • Findings contribute to advancing the field of human-robot interaction and robot design principles.