Bulanık mantık tekniği kullanılarak stres değerlendirme

Individuals face many events during their lives. The human body reacts to all kinds of events that the individual encounters. This nonspecific response of the body to unexpected conditions and any change is called stress. Since human's perspectives on events are not the same, their reactions may not be the same. Therefore, the stress levels of individuals can be different. In order to minimize the damage caused by stress, which is an inseparable part of life, the first step is to determine the stress level of the person. Biomedical methods and scales are frequently used to determine the stress level. However, thanks to the development of technology, methods of determining the stress level have spread to fields such as artificial intelligence, machine learning, image processing, and neural network. In this thesis, a model based on fuzzy logic techniques has been developed using photographs containing facial expressions in order to assess the stress levels of individuals. Basically, the difference between two photographs of the individual was used in the model. This difference was obtained from eye pair, mouth, forehead and eyebrow regions, which contain the important symptoms of stress on the human face and were detected using image processing. Fuzzy logic techniques used in the application are Fuzzy C-Means (FCM) clustering, Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy Inference System (FIS). In the final result obtained from the model was determined so that the stress level of the individuals was included in one of the "None", "Low", "Moderate" and "High" levels.