Stress detection system using sensors

In today’s fast-paced world, stress is one of the most common factors that impact physical and mental health. Ongoing exposure to stress can lead to serious health issues like high blood pressure, anxiety, depression, and heart disease. Traditional methods for assessing stress mostly rely on questionnaires and self-reports, which may not always give precise or timely results. To address these challenges, this project presents a Stress Detection System Using Sensors that uses physiological data to identify and monitor stress levels in an objective way. The proposed system incorporates wearable and biomedical sensors that track parameters such as heart rate, body temperature, and skin conductivity (GSR). These real-time signals are collected and processed with a microcontroller and analyzed using machine learning algorithms to classify the user’s stress level as low, moderate, or high. The processed data can be displayed on a mobile app or web interface, making it easy to monitor. This system is non-invasive, user-friendly, and able to provide continuous monitoring, making it suitable for everyday use in homes, offices, and healthcare settings. It allows for early detection of stress, enabling users to take preventive steps, such as practicing relaxation techniques or seeking medical advice. The proposed solution is affordable and scalable, making it a valuable addition to modern healthcare and wellness monitoring systems. Overall, this project aims to offer a reliable and accessible way to manage stress and encourage a healthier lifestyle through smart sensing technology.