A Fuzzy Logic Model for Stress Assessment

Abstract: Stress is a universal concept that concerns people of all ages, from young to old, and even all living things. It is important to detect it to protect itself from the negative effects of stress, which is intertwined with human life, or to benefit from its existence. In this study, a model based on fuzzy logic techniques which are some of the sub-branches of artificial intelligence has been developed using photographs containing facial expressions to assess the stress levels of individuals. Basically, the difference between two photographs of the individual was used in the model. Various fuzzy logic techniques which are Fuzzy C-Means (FCM) clustering, Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy Inference System (FIS) are used in proposed cascade model. In the result of the model, the stress level of the individuals was included in one of the “None”, “Low”, “Moderate” and “High” levels. The fuzzy model correctly assessed approximately 70% of the dataset used.

Keywords: Artificial intelligence, fuzzy logic techniques, fuzzy inference system, image processing, stress assessment