"Multimodal Image and Biosignal Dataset"

"Abstract (150 Words)Stress detection plays a vital role in monitoring an individual\u2019s physical and mental well-being. This study presents a structured multimodal dataset developed for stress level classification by integrating physiological parameters and image-based information. The dataset includes key attributes such as respiration rate, blood oxygen saturation (SpO\u2082), heart rate, and corresponding image paths, along with labeled stress levels. These features provide meaningful insights into the body\u2019s physiological responses under varying stress conditions. The dataset is designed to support the development and evaluation of machine learning and deep learning models for accurate and efficient stress prediction. By combining physiological signals with visual data, the dataset enhances the robustness and reliability of stress detection systems. It can be effectively used in applications such as healthcare monitoring, wearable systems, and affective computing. This dataset serves as a valuable resource for researchers aiming to develop intelligent, data-driven solutions for stress analysis and management."