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

Empathy02:34

Empathy

9.6K
Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor. 
9.6K

You might also read

Related Articles

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

Sort by
Same author

Development of an Educational Curriculum for the Surgical Implantation of DBS Systems.

Neuromodulation : journal of the International Neuromodulation Society·2026
Same author

Grand Challenges in Cross Reality.

IEEE transactions on visualization and computer graphics·2026
Same author

Wnt activation prevents epileptogenic hippocampal remodeling in animal models of unilateral and bilateral temporal lobe epilepsy.

bioRxiv : the preprint server for biology·2026
Same author

Renal tubular Nfe2l1 protect cisplatin-induced acute kidney injury via suppressing ACSL4-dependent ferroptosis.

Journal of advanced research·2026
Same author

Augmented Reality and Artificial Intelligence for the Assessment and Rehabilitation of Spatial Neglect: A Systematic Review.

Neurorehabilitation and neural repair·2026
Same author

Fine-scale urban-land configurations indirectly drive the strong spatial variability in pCO<sub>2</sub> and CO<sub>2</sub> fluxes in mountainous urban streams.

Environmental pollution (Barking, Essex : 1987)·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026
Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026
Same journal

Spatial-temporal Relation guided Motion Transfer via Diffusion Model.

IEEE transactions on visualization and computer graphics·2026
See all related articles

Related Experiment Video

Updated: Jul 1, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.4K

CAEVR: Biosignals-Driven Context-Aware Empathy in Virtual Reality.

Kunal Gupta, Yuewei Zhang, Tamil Selvan Gunasekaran

    IEEE Transactions on Visualization and Computer Graphics
    |March 4, 2024
    PubMed
    Summary
    This summary is machine-generated.

    This study shows Context-Aware Empathic Virtual Reality (CAEVR) enhances user experience by adapting to emotions. The research used physiological signals for real-time emotion recognition to improve virtual agent interactions.

    More Related Videos

    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality
    10:14

    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

    Published on: May 10, 2024

    966
    Virtual Reality Experiments with Physiological Measures
    07:09

    Virtual Reality Experiments with Physiological Measures

    Published on: August 29, 2018

    12.7K

    Related Experiment Videos

    Last Updated: Jul 1, 2025

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.4K
    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality
    10:14

    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

    Published on: May 10, 2024

    966
    Virtual Reality Experiments with Physiological Measures
    07:09

    Virtual Reality Experiments with Physiological Measures

    Published on: August 29, 2018

    12.7K

    Area of Science:

    • Human-Computer Interaction
    • Affective Computing
    • Virtual Reality

    Background:

    • Limited research exists on Virtual Reality (VR) applications recognizing and responding to user emotions.
    • Developing emotionally intelligent VR systems is crucial for enhancing user experience and interaction fidelity.

    Purpose of the Study:

    • To investigate the impact of Context-Aware Empathic VR (CAEVR) on users' emotional and cognitive experiences.
    • To explore the effectiveness of real-time emotion recognition models in personalized and generalized VR environments.
    • To assess the influence of an empathic virtual agent and an emotion-adaptive VR environment on user engagement and empathy.

    Main Methods:

    • Developed a real-time emotion prediction model using electroencephalography (EEG), electrodermal activity (EDA), and heart rate variability (HRV).
    • Implemented personalized and generalized emotion recognition models.
    • Integrated the emotion recognition model into a context-aware empathic (CAE) virtual agent and an emotion-adaptive (EA) VR environment.

    Main Results:

    • Significant increases in positive emotions and cognitive load were observed in users interacting with the CAEVR system.
    • Users demonstrated heightened empathy towards the context-aware empathic virtual agent.
    • The study identified key lessons learned and potential future research directions for empathic VR.

    Conclusions:

    • CAEVR systems show significant potential for refining user-agent interactions within virtual environments.
    • Real-time emotion recognition using physiological signals is a viable approach for creating adaptive and empathic VR experiences.
    • Further research is needed to optimize CAEVR for diverse applications and user groups.