ReviewRevista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)2025
Emotional recognition technologies applied to health: review and challenges.
Review in Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- The Role of Emotions in Health Literacy and Patient Education: Trends, Technologies, and Future Opportunities-A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Editorial: Advancing human wellbeing: environment-focused AI technologies.Frontiers in artificial intelligence · 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
10 authors.
Funding
Abstract
objectiveEmotions affect health and health affects emotions. When properly recognized and interpreted, emotions can aid in the prevention, diagnosis, and treatment of many diseases. Affective computing, the use of computer technology to detect one or more signals associated with human emotions, is a promising field. However, research into the use of emotion recognition in healthcare remains scarce. It is crucial to explore the reasons behind this phenomenon and identify neglected methods with potential for human health. We review methods and technologies used in emotion recognition and their applications in healthcare, highlighting methods not discussed in previous reviews, including electroencephalography and electrocardiography, thermal imaging, bracelets, skin conductance, and audio.
methodsA metric based on reproducibility and population was established to assess the quality of included articles. Based on the metrics established, we surveyed and analyzed studies in which affective computing tools were applied to health, to qualify and identify the challenges of the area.
resultsWe found many challenges to be overcome in detecting and recognizing human emotions, related to sample size, low study quality, and reproducibility issues. We list and discuss the main current challenges, ways to overcome them, and perspectives for the future, focusing on the application of affective technologies in healthcare and the establishment of a gold standard.
conclusionThree suggestions are proposed: 1) to conduct studies focused on obtaining a gold standard; 2) to conduct studies with larger sample sizes, greater diversity, and in less controlled environments, using replicable methodologies and making data and methods available; and 3) to further explore the potential use of emotion detection in healthcare.
Indexed as
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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.