Abstract—This article presents the design and simulation of an intelligent wearable device for real-time stress monitoring, developed in the MATLAB/Simulink environment. The primary goal is to create an energy-efficient and adaptable architecture that does not rely on onboard machine learning, yet still ensures the accurate detection of stress-related physiological changes. The proposed system integrates 10 biosensors, Field-Programmable Gate Array (FPGA)-based signal preprocessing, adaptive polling frequency control (1.5–10 Hz), and Stateflow-driven alarm logic. Key simulation results include realistic sensor responses, synchronized signal dynamics, and detailed power consumption modeling, partially validated using real hardware components. These findings demonstrate the system’s potential for low-power, real-time health monitoring and lay the groundwork for future physical implementation.
 
Keywords—wearable device, stress monitoring, sensory signals, MATLAB/Simulink, adaptive polling frequency


Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).