Stress classification based on human electromagnetic radiation analysis

Stress is a feeling of emotional or physical tension due to any events that makes one feel frustrated, angry or nervous. It a situation that trigger particular biological response when encounter a threat or challenge. This paper discussed stress classification based on human electromagnetic radiation (EMR). At first, the collected radiation frequency data is analyzed using multivariate analysis of variance (MANOVA) to identify the significance points for the classification. Then, the data is classified using locally weighted learning (LWL) algorithm. The results show stress classification using EMR based on third eye and throat chakra points obtained accuracy of more than 60%.