Affective Computing in Serious Games for Physical Rehabilitation: Scoping Review.

Background: Serious games have become an alternative support for traditional physical therapy. However, many of these games do not address the emotional needs of patients. People with disabilities often experience emotions such as sadness, frustration, and even anger, which can create a barrier to their rehabilitation treatment. Objective: This review presents a comprehensive overview of technologies, techniques, and methods in affective computing as applied to serious games for physical rehabilitation and identifies key gaps to guide future research in this field. Methods: A scoping review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, using the databases PubMed, ScienceDirect, IEEE Xplore, ACM Digital Library, PEDro, Springer, and Google Scholar. Results: The initial search yielded 5293 records, of which 9 papers met the inclusion criteria. Data were systematically extracted from these papers based on predefined research questions. Notably, engagement, tiredness, and pain were the most identified emotions, reported in 4 of 9 (50%) studies. Only 3 studies applied theoretical frameworks for emotion classification. Facial expression analysis and gesture recognition were the most frequently used affective computing techniques, yet only 2 studies implemented adaptive gameplay based on affective feedback. Conclusions: The integration of affective computing into serious games represents a promising approach for detecting affective states in patients undergoing rehabilitation. However, the limited number of primary studies, methodological limitations, and potential selection and reference-standard biases limit the reliability and generalizability of the current findings. Future research should prioritize rigorous multicenter designs, standardized evaluation protocols, and multidisciplinary collaboration. Developing these areas is essential to establishing clinical effectiveness.

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Journal
PubMed
Published
2026-07-02
DOI
https://doi.org/10.2196/81344
Primary Topic
Emotion and Mood Recognition
Type
article
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article

Affective Computing in Serious Games for Physical Rehabilitation: Scoping Review.

Erick I. Guerra-Hernández, Jaime Gutiérrez-Gutiérrez, Patricia Batres-Mendoza, María Del Pilar Beristain-Colorado et al.
PubMed
Emotion and Mood Recognition
article

Affective Computing in Serious Games for Physical Rehabilitation: Scoping Review.

Erick I. Guerra-Hernández, Jaime Gutiérrez-Gutiérrez, Patricia Batres-Mendoza, María Del Pilar Beristain-Colorado, Jorge Fernando Ambros-Antemate, José Luis Cano-Pérez, Marciano Vargas-Treviño, Christian Perezcampos-Mayoral
article en

Abstract

Background: Serious games have become an alternative support for traditional physical therapy. However, many of these games do not address the emotional needs of patients. People with disabilities often experience emotions such as sadness, frustration, and even anger, which can create a barrier to their rehabilitation treatment. Objective: This review presents a comprehensive overview of technologies, techniques, and methods in affective computing as applied to serious games for physical rehabilitation and identifies key gaps to guide future research in this field. Methods: A scoping review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, using the databases PubMed, ScienceDirect, IEEE Xplore, ACM Digital Library, PEDro, Springer, and Google Scholar. Results: The initial search yielded 5293 records, of which 9 papers met the inclusion criteria. Data were systematically extracted from these papers based on predefined research questions. Notably, engagement, tiredness, and pain were the most identified emotions, reported in 4 of 9 (50%) studies. Only 3 studies applied theoretical frameworks for emotion classification. Facial expression analysis and gesture recognition were the most frequently used affective computing techniques, yet only 2 studies implemented adaptive gameplay based on affective feedback. Conclusions: The integration of affective computing into serious games represents a promising approach for detecting affective states in patients undergoing rehabilitation. However, the limited number of primary studies, methodological limitations, and potential selection and reference-standard biases limit the reliability and generalizability of the current findings. Future research should prioritize rigorous multicenter designs, standardized evaluation protocols, and multidisciplinary collaboration. Developing these areas is essential to establishing clinical effectiveness.

PubMedVol. 13
Benito Juárez Autonomous University of Oaxaca (MX)
Openalex Percentile: Top 24%
Emotion and Mood Recognition
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