Development of a Heart Rate Variability-Based Predictive Model for Depressive Symptoms in Chinese University Students

> .05), with over 91% of the predicted scores falling within the 95% confidence interval of the actual scores. The strong correlation between HRV and SDS scores supports the use of HRV as a reliable indicator for depression screening. Overall, the model demonstrated a prediction accuracy of 92.61%, highlighting its potential for objective mental health assessment among university populations.