A Fuzzy Logic Model for Human Distress Detection

Abstract

Distress occurs when a person is in anxiety or fear. Existing research in distress detection arising from physical attacks focused mainly on the use of machine learning techniques. To extend research efforts, this study proposes an alternate approach using fuzzy logic. Parameters to describe physically triggered distress were identified and used as input to the designed fuzzy model. Experiments were carried out using random samples of data values to test the behavior of the model. In all cases, the model was able to show outcomes that are expected and achieved high accuracy.