AI Driven Psychological Pattern Analysis through Deep Learning-Enhanced Wearable Monitoring Systems

Quantitative research on tension environments has mostly used mobile assessment experiments in standardized settings. Recently, sensors and eye-tracking glasses have dedicated resources to future technologies, including multisensory monitoring systems that contain psychophysiological data in daily circumstances. This research proposes a Deep Learning aided wearable monitoring system (DLWMS) for psychological pattern analysis and mobile phone stress monitoring. Such systems must analyze stress states in mobile situations and look for tension parameter fluctuations. Using advanced quantitative monitoring system devices to collect physiological data on customers may help researchers study information systems (IS), which conventional treatments do not use. Participants demonstrate the possibility and acceptability of using m-Health technologies for psychophysiological health education. This approach helps prospective studies evaluate these technologies for optimizing safety in this sensitive population.