AI-based Model for Physio-Psycho Behavior of University Students - Chahar, Shubham; Arora, JK; Kumar, Utkarsh (International Journal of Computer Sciences and Engineering, 2023)
Artificial Intelligence (AI) has emerged as a powerful tool for measuring the psychophysiological behavior of students, enabling a deeper understanding of their cognitive and emotional states. By leveraging AI algorithms and data analytics, researchers can analyze various data sources such as facial expressions, voice tone, eye movements, and physiological signals to infer students` engagement levels, attention spans, stress levels, and overall emotional well-being. This technology has applications in educational settings, where AI can be utilized to develop intelligent tutoring systems that adapt to students’ individual needs, providing personalized feedback and interventions. Yoga and have gained significant popularity in recent years due to their potential positive effects on physical, mental, and emotional well-being. This research paper explores the effects of yoga on the psychological and physiological well-being of university students, using an Artificial Neural Network (ANN) model. The study aims to analyze the relationship between regular yoga practice and various indicators of well-being among students. The ANN model is employed to uncover complex patterns and interactions within the dataset, providing insights into the potential benefits of these practices. The findings of this research have implications for promoting holistic well-being among university students. A sigmoid axon was used as a transfer function for input and output layers.