ArticleScientific reports2025
Feasibility study of emotion mimicry analysis in human-machine interaction.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Emotion Recognition from Facial Expressions Considering Individual Differences in Emotional Intelligence.Biomimetics (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Health apps have increased in popularity as people increasingly follow the advice these apps provide to enhance physical and mental well-being. One key aspect of improving neurosensory health is identifying and expressing emotions. Emotional intelligence is crucial for maintaining and enhancing social interactions. In this context, a preliminary closed-loop feedback system has been developed to help people project specific emotions by altering their facial expressions. This system is part of a research intervention aimed at therapeutic applications for individuals with autism spectrum disorder. The proposed system functions as a digital mirror, initially displaying an animated avatar's face expressing a predefined emotion. Users are then asked to mimic the avatar's expression. During this process, a custom emotion recognition model analyzes the user's facial expressions and provides feedback on the accuracy of their projection. A small experimental study involving 8 participants tested the system for feasibility, with avatars projecting the six basic emotions and a neutral expression. The study results indicated a positive correlation between the projected facial expressions and the emotions identified by participants. Participants effectively recognized the emotions, with 85.40% accuracy demonstrating the system's potential in enhancing the well-being of individuals. The participants were also able to mimic the given expression effectively with an accuracy of 46.67%. However, a deficiency in the performance of one of the expressions, surprise, was noticed. In the post processing, this issue was addressed and model enhancements were tailored to boost the performance by ~ 30%. This approach shows promise for therapeutic use and emotional skill development. A further wider experimental study is still required to validate the findings of this study and analyze the impact of modifications made.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.