Systematic review reveals an evolution from self-report to multimodal AI emotion measurement tools in design, indicating a shift toward hybrid tracking systems.
Emotions are central to human experience and increasingly important in design, yet their systematic measurement and integration into design processes remain poorly understood. This study conducts a hybrid systematic–bibliometric review of 236 peer-reviewed articles published between 2000 and 2025, identifying 38 emotion measurement tools and examining their evolution, methodological foundations, and applicability to design. Following a PRISMA-based screening procedure, bibliometric and thematic analyses were conducted. The tools were categorized according to assessment method, placement within the design process, and contextual domain. Findings reveal that although self-report methods dominate, physiological and observational approaches offer greater reliability but limited feasibility. The study also presents a conceptual framework outlining the evolution of tools from early self-report instruments to current AI- and multimodal-based systems, demonstrating a shift toward hybrid and technology-enabled approaches. By providing an understanding of the current landscape of emotion measurement, this research supports the development of next-generation tools.
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Tohidifar et al. (2026) studied this question.
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