Human Stress

Human stress research focuses on understanding its multifaceted nature and impact, encompassing physiological, psychological, and behavioral responses. Current investigations utilize diverse methods, including multimodal sensor data analysis (often employing machine learning algorithms like neural networks, including CNNs and LSTMs, and Random Forests) and computational modeling of physiological processes (e.g., active inference frameworks), to identify reliable stress biomarkers and predict stress levels. These efforts aim to improve stress detection and management, with applications ranging from mental health assessment to human-robot interaction and even financial market prediction. The ultimate goal is to develop more effective tools for stress mitigation and improved well-being.