Prediction and Classification of Stress in Humans

Abstract

To avoid serious health problems, researchers are working difficult to come up with effective methods for detecting and coping with excessive amounts of stress. Facial gestures are an essential part of human speech. Researchers in psychology, computer science, neuroscience, and other fields are increasingly interested in a human-computer interface device for automated face recognition or facial expression recognition. as well as similar areas. The machine identifies frontal faces in photographs and codes each frame according to a series of dimensions. A system for acquiring the corresponding information is inside this case of sentiment classification utilizing a biologic output or a thermodynamic picture, which was being used, it is necessarily researched extensively. To develop efficient strategies for identifying and controlling elevated levels of stress in order to reduce severe health effects. Facial gestures are an essential part of human speech. Researchers are particularly involved in a human-computer interface device for automated face recognition or facial expression recognition. In the photographs, the machine senses frontal facesand codes each frame according to certain dimensions. Experimentation indicate that the proposed algorithm can detect more efficient action