Assessment of a Coordinated Arrangement of Wearable Physiological Sensors for Stress Checking in Work Spaces by Utilizing Organic Markers

Abstract

The objectives of this investigation were to create and evaluate a wearable physiological sensor system for detecting human stress using ECG, EDA, and EEG data, as well as to see if the changes in physiological indicators were correlated levels. The main elements of the study are listed below. This study included 15 healthy volunteers with an average age of 40.8 years, comprising seven men and six women. They underwent the well-known Maastricht Intense Stress Test, a procedure that is known to cause significant physical and psychological stress, while wearing three commercial sensors have been employed to keep track of their physiologic responses.Throughout salivary samples were taken at various points. The use of a Salivary concentrations of cortisol were correlated with the obtained physiological indicators using an algorithm called the Support Vector Machine (SVM) segmentation technique were both part of the statistical analysis. A significant ability to discriminate between stress and relaxation was shown by fifteen features obtained from measurements including heart rate variability, electro dermal activity, and electroencephalography signals. Based on these important features, the classification system produced results with an accuracy rate of 86% that was satisfactory.Furthermore, the correlation analysis revealed, with an R-squared value of 0.714, a considerable consistency between changes in physiological characteristics and the trends in salivary cortisol levels. The study successfully showed that the wearable sensor system's implementation caught human stress levels and measured the state of stress with accuracy. The design of adaptable and controllable systems, such as medical devices, targeted at inducing interventions to stop stress-related effects, is particularly affected by these findings.