A Comprehensive Review on Fuzzy Logic-Based Models for Stress Detection

Abstract

Individuals naturally experience stress on a regular basis. It causes the production of hormones that assist to handle any circumstances, however long-term stress has adverse impacts on wellness and may cause symptoms such as headaches, insomnia and depression. For this reason, early identification of stress is crucial to preventing these negative impacts. This paper provides a comprehensive review on various fuzzy Inference Systems (FIS) models for stress detection. The scholarly articles which have been published from 2022 to 2026 are considered in this work. Moreover, this paper mainly focused on those stress detection models which have been developed by using fuzzy logic. A comparison study of existing best fuzzy logic-based systems is offered after a comprehensive literature review. This paper reviewed publications which used psychological, behavioural and physiological inputs to investigate conventional and mixed fuzzy system. The work investigated how well fuzzy models, like Mamdani, handle non-linear stress variables. During this study, it is analyzed that fuzzy logic offers excellent performance for the identification of stress at its early phases. Moreover, the discussion concludes by outlining the present issues, limits and opportunities for further stress detection research using fuzzy logic.