Adaptive Systems for Well-being Promotion: A Systematic Mapping
DOI:
https://doi.org/10.5753/jbcs.2026.4994Keywords:
Well-being, Adaptive system, Physiological sensors, Systematic mappingAbstract
Research on Human-Computer Interaction (HCI) interfaces has gained increasing relevance in both corporate and academic environments, particularly in adaptive systems that offer personalized interventions. Adaptive systems are crucial for enhancing user experience and promoting well-being by dynamically adjusting to individual needs and contexts. Well-being, which encompasses physical, mental, and social dimensions, can significantly influence user behavior and task performance. However, measuring well-being remains a complex challenge due to its subjective and multidimensional nature. This study aims to map and analyze the state of the art in computational interfaces that adapt to the user’s context to promote well-being. Specifically, the study addresses the gap in adaptive systems, which are still underdeveloped in the field. Despite significant progress in measuring well-being, most systems focus on monitoring well-being states or training predictive models, rather than offering fully adaptive interventions. To explore this, a systematic mapping study was conducted, investigating three key questions: What is the purpose of the study regarding the well-being dimension explored, as well as the approaches and techniques used to promote it? What methods were employed to measure users’ well-being? What interventions were implemented to promote well-being? The analysis of 36 selected studies reveals that research primarily concentrates on the mental and physical dimensions of well-being, with artificial intelligence techniques and physiological sensors, particularly electrocardiograms (ECG), being the most frequently used. However, there is a notable lack of adaptive systems in the literature. These findings underscore the need for further development of adaptive interventions that actively improve well-being, providing valuable insights to guide the design of adaptive interfaces. By leveraging these insights, future systems can be developed to enhance user experience and promote well-being across diverse domains.
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Copyright (c) 2026 Alex Sandro Rodrigues Ancioto, Fabiana Luci de Oliveira, Vânia Paula de Almeida Neris
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