As technology advances, the application of Virtual Reality (VR) in the field of mental health continues to grow, particularly showcasing its unique advantages in the adjustment and treatment of emotional and psychological states. Traditionally, the diagnosis of depression relies on clinical psychologists who assess symptoms through conversation and behavioral observation, supported by standardized psychological assessment tools. These methods rely primarily on subjective reports and the judgment of clinicians, which can lead to inconsistencies and reproducibility problems in the diagnosis results. This study utilizes VR technology combined with physiological measurement tools to explore and analyze the emotional response differences between depressed patients and healthy individuals while watching VR videos with different emotional colors, and attempts to predict the state of depression. Forty-six participants are exposed to three types of emotionally colored videos in a VR environment. The correlation between electrodermal activity (EDA), heart rate, and depression is investigated. The results indicate significant differences in psychological and physiological responses between depressed patients and healthy individuals, suggesting these differences could serve as new biomarkers for the diagnosis and prediction of depression. This study extends the application of VR technology in mental health assessments, providing a scientific basis for more objective diagnostic and predictive methods for depression, potentially enhancing the accuracy and efficiency of diagnosis and prediction.