This research undertakes a comparative analysis of baseline and recovery Electrocardiogram (ECG) data to assess the cardiovascular effects of cognitive stress on Unmanned Aerial Vehicle (UAV) operators. It involves 24 subjects from diverse aviation backgrounds who participated in simulated UAV operations. The research aims to evaluate physiological responses by analyzing ECG data collected before and after stress-inducing activities, utilizing statistical methods such as the Z-transform for data normalization and the Student’s T-test to analyze differences between pre- and post-simulation heart rate variability (HRV). The findings indicate significant changes in HRV as a result of stress during the simulations, underscoring the importance of monitoring physiological responses to better understand cognitive workload. The experiment involved two flights with different Human-Machine Interface (HMI) configurations, such as voice command use and multi-operator settings, to simulate stress conditions. Baseline ECG signals were recorded before the simulation, and recovery signals were recorded afterward, with heart rate data analyzed through statistical methods. The results demonstrated consistent differences between the baseline and recovery states for most participants, indicating that cognitive stress substantially affected cardiovascular metrics. As future work, investigations could expand to include other physiological indicators, such as galvanic skin response and eye-tracking data, for a more holistic view of cognitive stress in UAV operations. Additionally, artificial intelligence models could be developed to better interpret these physiological responses, ultimately enhancing the design of human-machine interfaces in high-stress environments.