Stress Detection by Deep Learning Technique

Stress is a natural response of the body to challenging situations or demands, whether they are physical or psychological in nature. It is a condition of emotional or mental stress that can be brought on by a number of things, including pressure from the workplace, worries about money, relationships, health, or significant life events. It's important to recognize symptoms of stress and take steps to manage stress before it starts to have a negative impact on our health and wellbeing. Several existing solutions exist for detecting stress levels, such as Natural Language Processing (NLP), speech analysis, image, and video analysis, etc., to detect the stress level of a person based on machine learning. This method is based on Convolution Neural Networks (CNNs). CNN is a kind of deep learning technique that works well for analyzing pictures and videos. CNNs can be used for stress detection by analyzing image and video data to identify physical markers of stress, such as changes in facial expressions, posture, and eye movements, as involving CNNs the accuracy of an algorithm will be improved to a greater extent. This research investigates the use of deep learning methods to identify stress in individuals.